AbsIDconvert:

An

absolute

approach

for

converting

genetic

identifiers

at

different

granularities

Background:

High-throughput

molecular

biology

techniques

yield

vast

amounts

of

data,

often

by

detecting

small

portions

of

ribonucleotides

corresponding

to

specific

identifiers.

Existing

bioinformatic

methodologies

categorize

and

compare

these

elements

using

inferred

descriptive

annotation

given

this

sequence

information

irrespective

of

the

fact

that

it

may

not

be

representative

of

the

identifier

as

a

whole.

Results:

All

annotations,

no

matter

the

granularity,

can

be

aligned

to

genomic

sequences

and

therefore

annotated

by

genomic

intervals.

We

have

developed

AbsIDconvert,

a

methodology

for

converting

between

genomic

identifiers

by

first

mapping

them

onto

a

common

universal

coordinate

system

using

an

interval

tree

which

is

subsequently

queried

for

overlapping

identifiers.

AbsIDconvert

has

many

potential

uses,

including

gene

identifier

conversion,

identification

of

features

within

a

genomic

region,

and

cross-species

comparisons.

The

utility

is

demonstrated

in

three

case

studies:

comparative

genomic

study

mapping

plasmodium

gene

sequences

to

corresponding

human

and

mosquito

transcriptional

regions;

cross-species

study

of

Incyte

clone

sequences;

and

analysis

of

human

Ensembl

transcripts

mapped

by

Affymetrix

and

Agilent

microarray

probes.

AbsIDconvert

currently

supports

ID

conversion

of

species

for

a

given

list

of

input

identifiers,

genomic

sequence,

or

genome

intervals.

Conclusion:

AbsIDconvert

provides

an

efficient

and

reliable

mechanism

for

conversion

between

identifier

domains

of

interest.

The

flexibility

of

this

tool

allows

for

custom

definition

identifier

domains

contingent

upon

the

availability

and

determination

of

a

genomic

mapping

interval.

As

the

genomes

and

the

sequences

for

genetic

elements

are

further

refined,

this

tool

will

become

increasingly

useful

and

accurate.

AbsIDconvert

is

freely

available

as

a

web

application

or

downloadable

as

a

virtual

machine

at:

to

assign

their

own

custom

generated

identifiers

(IDs)

to

the

biological

entities.

Major

public

databases

such

as

GenBank

and

RefSeq

use

accession

numbers,

Gene

Ontology

(GO)

uses

a

naming

convention

from

organism

specific

databases,

the

HUGO

(Human

Genome

Organization)

Gene

Nomenclature

Committee

(HGNC)

uses

the

gene

symbol

and

a

custom

generated

ID,

Entrez

uses

numeric

integers,

sequencing

projects

use

systematic

names

and

biologists

sometimes

use

additional

aliases.

As

an

example,

the

breast

cancer

early

onset

gene

has

the

official

gene

symbol

of

provided

by

HGNC

and

an

associated

ID

Ensembl

gene

ID

OMIM

(Online

AbsIDconvert

is

the

only

known

gene

ID

conversion

tool

based

on

genomic

coordinates/intervals

of

which

we

are

aware.

This

is

a

novel

and

important

contribution

in

the

realm

of

gene

ID

conversion

due

to

the

large

variety

of

genetic

entities

in

current

use

by

biologists,

the

need

to

convert

between

them,

and

the

fact

that

most

biological

entities

(nucleic

acid,

protein

entities

etc.)

have

an

associated

sequence.

Mapping

of

the

entity

sequence

to

a

reference

genome

sequence

provides

the

concomitant

genomic

interval

that

allows

determination

of

other

entities

that

have

overlapping

genomic

intervals..

The

interval

basis

of

AbsIDconvert

provides

ease

of

flexibility

with

respect

to

any

additions,

deletions

or

updates

of

the

underlying

objects,

requiring

only

adding

of

intervals,

removing

intervals,

or

modifying

the

intervals

themselves,

respectively.

This

makes

it

possible

to

easily

keep

the

structure

updated

as

the

current

state

of

biological

knowledge

changes.

A

major

update

is

only

required

when

the

underlying

genome

changes,

a

fairly

rare

occurrence

for

most

organisms,

especially

when

compared

to

how

often

other

genomic

databases

are

modified..

These

intervals

also

allow

easy

discovery

of

genetic

entities

that

only

partially

overlap

with

queried

IDs/intervals,

or

that

are

within

a

specified

distance

nearby.

More

frequently,

researchers

are

interested

in

those

genes

that

are

near

specific

genomic

intervals

corresponding

to

various

types

of

genetic

control

elements

such

as

transcription

factor

binding

sites,

enhancers,

untranslated

regions,

and

hyper/hypo

methylated

regions.

AbsIDconvert

makes

it

easy

to

find

those

entities

that

overlap

or

lie

nearby

regions

of

interest.

With

the

incorporation

of

a

sequence

mapping

algorithm,

AbsIDconvert

integrates

the

determination

of

genomic

intervals

for

any

supplied

sequence,

making

it

possible

to

easily

find

and

convert

between

IDs

from

any

platform

and

organism,

such

as

the

examination

of

correspondence

of

the

human

EST

clones

with

rat

and

mouse

genes

(case

study

and

of

plasmodium

and

human

genes

(case

study

We

do

not

know

of

any

other

system

that

can

easily

accomplish

these

types

of

analyses..

AbsIDconvert

can

greatly

facilitate

the

work

of

those

who

are

involved

in

meta

analyses

studies.

When

comparing

studies

where

either

the

species

and

or

platform

varies,

this

methodology

will

have

clear

advantages

over

others

as

it

is

based

on

common

genomic

coordinates..

The

use

of

an

interval

tree

structure

makes

it

possible

to

perform

large

conversions

quickly

and

efficiently.

This

method

is

efficient

while

dealing

with

genomic

intervals

and

has

a

significant

advantage

over

other

methods

such

as

relational

databases.

Although

theoretically

limited

by

working

memory,

of

the

interval

trees

generated

and

used

by

AbsIDconvert

require

more

than

of

RAM

on

the

deployed

server,

with

the

majority

being

rather

small

in

size

(less

than

MB).

If

the

data

cannot

fit

into

main

memory,

a

method

such

as

that

proposed

by

Arge

et

al.

can

be

used

that

maintains

the

interval

tree

in

secondary

memory

efficiently..

AbsIDconvert

is

provided

as

a

web

page

at

and

is

also

available

as

a

virtual

machine

for

those

wishing

to

run

a

local

instance.

Future

work

will

include

providing

command

line

access,

a

RESTful

interface,

and

modifying

the

interface

to

utilize

a

workflow

management

tool

for

genomic

data

such

as

GALAXY,

where

the

primary

data

units

are

genomic

sequences

and

intervals.

the

Paralyzed

Veterans

of

America

(fellowship

to

BJH)

and

by

the

Kentucky

Spinal

Cord

and

Head

Injury

Research

Trust

(JCP).

Its

contents

are

solely

the

responsibility

of

the

authors

and

do

not

represent

the

official

views

of

the

funding

organizations.

The

Nucleic

Acid

Research

(NAR)

database

issue

features

databases

covering

various

aspects

of

molecular

biology

including

sequences,

gene

expression,

structures,

pathways

and

diseases.

Most

of

these

databases

are

independent

of

each

other

and

have

been

created

as

a

result

of

the

respective

developers'

domain

of

interest

and

resource

limitations.

Due

to

a

lack

of

standard

naming

conventions,

most

of

these

databases

Mendelian

Inheritance

in

Man)

ID

HPR

(Human

Protein

Reference)

database

ID

Ref-Seq

ID

NM

GenBank

Accession

Entrez

Gene

ID

VEGA

(the

Vertebrate

Genome

Annotation

database)

gene

ID

UCSC

gene

ID

UniProt

ID

and

gene

aliases

FAD,

FACD,

FANCD..

Fortunately,

there

is

a

wealth

of

information

available

to

the

research

community

in

a

wide

variety

of

databases.

However,

it

is

often

difficult

to

extract

or

integrate

information

about

a

particular

biological

entity

from

multiple

resources.

For

instance,

a

researcher

may

be

interested

in

extracting

functional

information

spread

across

different

databases

for

a

biological

entity

such

as

a

gene

or

a

protein;

comparing

two

independent

pathways

which

use

different

types

of

identifiers;

or

comparing

results

across

species,

platforms

or

labs.

The

lack

of

a

common

identifier

across

these

heterogeneous

and

sometimes

redundant

biological

databases

makes

the

functional

analysis

of

biological

data

tedious,

time

consuming,

and

error

prone..

One

solution

to

handle

heterogeneous

databases

is

to

use

a

global

identifier

for

annotations

such

as

the

one

described

by

MIRIAM

(Minimum

Information

Requested

In

the

Annotation

of

biochemical

Model)

MIRIAM

requires

a

global

identifier

to

contain

both

the

data

source

as

well

as

an

internal

identifier.

For

example,

is

composed

of

urn:miriam

that

defines

the

notation

to

be

a

URN

(Uniform

Resource

Name)

using

the

MIRIAM

scheme

with

data

type

hgnc

and

identifier

This

method

appears

promising

and

has

the

potential

to

solve

some

of

the

previously

mentioned

problems,

but

very

few

databases

follow

this

standard.

Another

solution

is

to

manually

search

for

these

genes

one

by

one

in

publicly

available

databases

such

as

Entrez,

KEGG

or

GEO

and

infer

their

functionality.

This

method

is

fruitful

when

the

number

of

genes

is

small,

but

is

impractical

for

high

throughput

experiments,

where

the

number

of

gene

fragments

can

be

on

the

order

of

tens

of

thousands

or

more.

A

third

solution

is

to

use

an

ID

converter

tool

that

uses

a

database

to

store

all

possible

annotations

where

a

list

of

IDs

may

be

input

as

a

query

which

is

then

converted

into

the

corresponding

target

IDs

in

a

precise

and

efficient

way..

One

difficulty

in

the

development

and

maintenance

of

such

conversion

tools

is

the

varying

granularity

of

the

identifiers.

More

specifically,

the

data

generated

by

biological

experiments

may

be

at

the

locus,

transcript,

sequence

or

probe

level,

with

varying

coverage

of

a

region

of

interest

Figure

This

granularity

ranges

from

very

fine,

at

the

level

of

DNA

microarrays

(tens

of

bases

in

length,

containing

probe

level

information

relevant

to

only

a

short

region

of

the

corresponding

mRNA

molecule)

through

coarser

granularity

with

sequence

reads

(few

hundreds),

transcripts

(thousands),

loci,

and

chromosomes.

It

is

also

possible

that

annotations

at

the

same

level

may

have

different

granularities.

For

example,

among

DNA

microarray

probes,

Affymetrix

probes

are

usually

short

bases)

whereas

Agilent

probes

are

longer

bases)

and

cDNA

probes

are

generally

nucleotides

in

length.

The

relationships

between

entities

at

the

same

or

different

granularities

may

be

either

or

n-m:

for

example,

an

Affymetrix

probe

may

span

more

than

one

EST;

more

than

one

such

probe

may

be

contained

inside

an

EST;

a

cDNA

probe

may

contain

zero,

one

or

more

Affymetrix

and

Agilent

probes..

Another

difficulty

in

the

development

of

such

tools

is

the

dynamic

nature

of

annotations.

Of

late,

rapid

advances

in

sequencing

and

their

declining

costs

have

enabled

researchers

to

perform

novel

sequencing

as

well

as

resequencing

projects.

These

result

in

an

increased

depth

of

coverage

of

a

genomic

sequence,

with

gaps

being

filled

and

repeats

more

accurately

mapped.

Sometimes,

the

sequence

underlying

a

genetic

entity

may

change,

and

on

a

less

frequent

basis

the

whole

genomic

sequence

needs

to

be

updated

(as

of

August

st

the

currently

available

genome

versions

for

human,

mouse

and

rat

are

and

(RGSC

respectively).

These

changes

may

modify

the

structural

and

functional

annotations

of

a

genetic

entity

(GenBank,

Ref-Seq

and

Ensembl

are

updated

everyday).

Frequent

updates

in

annotations

also

create

problems

in

the

manufacturing

of

DNA

microarrays.

Microarray

chips

are

designed

and

their

probes

are

annotated

using

the

current

build

of

a

specific

genome.

Regardless

of

the

care

taken

in

this

design,

the

system

will

include

flaws

due

to

the

combination

of

the

delay

inherent

in

the

process

of

microarray

designmanufacture-deployment

(compounded

by

the

latency

to

use)

and

the

dynamic

nature

of

annotations.

Attempts

to

address

these

problems

have

been

the

focus

of

a

number

of

previous

studies.

Gautlier

et

al.

found

redundancies

in

the

annotations

of

Affymetrix

probes

at

a

sequence

level

that

map

to

multiple

RefSeq

genes.

Such

ambiguities

may

result

in

inaccurate

interpretations.

AffyProbeMiner

uses

RefSeq

and

GenBank's

validated

complete

coding

sequences

to

regroup

the

probes

on

an

Affymetrix

chip

into

consistent

probe

sets.

In

their

study,

regrouping

of

the

probes

affected

almost

of

the

probes

on

the

chip.

Harbig

et

al.

reidentified

the

Affymetrix

plus

GeneChip

array

probes

in

an

attempt

to

increase

the

reproducibility

of

microarray

experiments.

They

used

BLAST

to

remap

the

probes

against

the

genome

and

redefined

approximately

of

the

probes.

These

studies

suggest

that

redefinition

or

reorganization

of

probesets

will

improve

the

analytical

accuracy

of

the

microarray

data,

a

process

that

would

be

greatly

facilitated

by

a

means

for

high-throughput

query

and

mapping/comparison

of

given

sequences

(such

as

microarray

probes)

to

other

genomic

annotations

stored

across

a

wide

variety

of

databases.

The

design

of

AbsIDconvert

was

accomplished

using

a

preprocessing

and

a

query

step.

In

the

preprocessing

step,

reference

genomes

were

downloaded

from

the

UCSC

Genome

Browser

ucsc.edu/downloads.html)

and

the

NCBI

website.

The

sequence

information

for

a

variety

of

identifiers

at

different

granularities

such

as

probes,

sequences

(ESTs),

transcripts

and

genes

were

downloaded

from

their

respective

authoritative

websites

or

UCSC.

The

identifier

types

include

Affymetrix

probes,

Agilent

probes,

EST

sequences,

Ensembl

transcripts

and

Entrez

genes.

Each

identifier

sequence

was

mapped

to

the

respective

genome

using

either

BLAT

or

Bowtie

BLAT

was

used

to

map

longer

BP)

sequences,

while

Bowtie

was

used

for

relatively

short

BP)

sequences

such

as

Figure

AbsIDconvert

technique.

Absolute

ID

conversion

is

a

two

step

process

whereby

probe

A

can

be

converted

to

identifiers

at

the

transcript

level

by

first

converting

the

probe

to

its

genomic

coordinates

(step

and

then

determining

transcripts

that

overlap

the

coordinate

positions

(step

Affymetrix

and

Agilent

probes.

Each

identifier

was

then

annotated

with

structural

information

such

as

start

(identifier's

start

coordinate

on

genome),

end

(the

end

coordinate

on

the

genome),

size

(sequence

size)

and

chrom

(corresponding

chromosome).

This

information

was

collected

for

each

identifier

as

a

genomic

interval.

Genetic

entities

with

multiple

exons

such

as

transcripts

were

treated

differently

as

there

are

two

ways

in

which

these

can

be

structurally

annotated.

One

method

is

to

use

the

extreme

ends

(i.e.

start

and

end

codons

of

the

transcript)

as

their

intervals

including

both

the

exons

as

well

as

intronic

regions,

or

alternatively

exclude

the

intronic

regions

and

assume

the

transcript's

genomic

intervals

are

an

assembly

of

genomic

intervals

of

the

participating

exons

(AbsIDconvert

incorporates

both).

Finally

organism

and

identifier

type

specific

interval

trees

were

constructed

and

stored.

A

list

of

all

identifiers

and

their

type

was

also

stored

in

a

relational

database

to

facilitate

batch

look-up

for

the

types

of

identifiers.

Figure

shows

the

design

steps

of

AbsIDconvert..

Once

structural

annotation

for

each

of

the

identifiers

is

available,

AbsIDconvert

can

query

this

information.

This

query

step

uses

the

structural

annotation

information

of

each

identifier

and

the

organism

specific

database

generated

from

the

previous

step.

AbsIDconvert

assumes

two

biological

entities

(nucleic

acid,

protein

entity)

are

the

same

if

their

genomic

sequences

are

also

the

same,

overlap

or

one

is

contained

within

the

other.

As

the

number

of

annotations

are

large

and

frequent

insertions

and

deletions

are

routine,

an

efficient

data

structure

for

storage

and

computational

operations

is

needed.

Considering

that

the

structural

annotation

is

in

the

form

of

genomic

intervals,

a

modified

Red-Black

tree,

known

as

an

interval

tree,

is

used

to

store

the

information

for

all

IDs.

An

interval

tree

maintains

a

dynamic

set

of

elements,

with

each

element

x

containing

an

interval

int

[x]

This

int[x]

stores

the

start

and

end

of

the

interval

apart

from

other

auxiliary

information.

This

data

structure

is

dynamic

in

nature

and

can

perform

insertions

and

deletions

efficiently

in

time

O(log

n),

where

n

is

the

number

of

elements.

Interval

trees

have

been

shown

to

be

efficient

for

working

with

a

large

number

of

genomic

intervals

There

are

four

possible

ways

in

which

AbsIDconvert

may

be

queried:.

Lookup

identifiers:

Given

a

mixed

list

of

identifiers,

AbsIDconvert

can

determine

the

types

of

identifiers

in

the

list.

This

step

uses

the

relational

database

created

in

the

preprocessing

step

and

can

efficiently

categorize

the

IDs

in

the

list.

Batch

conversion

of

IDs:

Given

a

list

of

identifiers,

AbsIDconvert

uses

the

interval

tree

to

find

their

genomic

coordinates.

Once

the

coordinate

information

is

available,

all

overlapping

identifiers

can

be

found

by

querying

the

interval

tree.

This

uses

the

IRanges

and

GenomicRanges

packages

internally

to

maintain

the

genomic

intervals

which

are

based

on

Allen's

Interval

Algebra

Users

can

specify

various

range

parameters

using

the

interface.

The

overlap

type

('type')

parameter

may

take

any

one

of

'any',

'start',

'end',

'equal'

or

'within'

as

its

value.

By

default

'any'

overlap

is

accepted.

If

'type'

value

is

'start'

or

'end'

then

the

query

intervals

are

required

to

have

matching

'start'

and

'end'

respectively

with

subject

intervals

in

the

database.

If

'type'

is

'equal'

B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Ship speed optimization: Concepts, models and combined speed-routing scenarios Psaraftis, Harilaos N.; Kontovas, Christos A.The purpose of this paper is to clarify some important issues as regards ship speed optimization at the operational level and develop models that optimize ship speed for a spectrum of routing scenarios in a single ship setting. The paper's main contribution is the incorporation of those fundamental parameters and other considerations that weigh heavily in a ship owner's or charterer's speed decision and in his routing decision, wherever relevant. Various examples are given so as to illustrate the properties of the optimal solution and the various trade-offs that are involved. In recent years, increasing fuel prices, depressed market conditions and environmental issues as regards air emissions from ships have brought a new perspective to ship speed. If this perspective had not received much emphasis in the past, this is not so today, and it will receive even more attention in the future. In addition to being efficient from an economic perspective, a ship also has to be environmentally friendly as regards air emissions. To that end, significant regulatory activity is already taking place within the International Maritime Organization (IMO) and other bodies. Such activity aims to cover the whole range from technical to operational to market-based measures and a wide spectrum of emissions, from greenhouse gases (GHGs) such as carbon dioxide (CO 2 ), to non-GHG gases such as sulphur oxides (SO x ), nitrogen oxides (NO x ), particulate matter (PM) and others.. Because of the non-linear relationship between speed and fuel consumption, it is obvious that a ship that goes slower will emit much less than the same ship going faster. It that sense, the impact of a change in ship speed on both ship operating costs and emissions can be quite dramatic. This can be manifested at two levels, the design level and the operational level.. At the design level, Maersk's new 18,000 TEU 'Triple-E' 2 containerships have a design speed of 17.8 knots, down from the 22 -25 knots range that has been In practice, super slow steaming has been pioneered by Maersk Line after it initiated trials involving 110 container vessels beginning in 2007. These trials showed that it was safe to reduce the engine load to as low as 10%, compared with the traditional policy of reducing the load to no less than 40%-60% (Tradewinds, 2009) . Given the non-linear relationship between speed and power, for a containership a 10% engine load means sailing at about half of the design speed. Slow steaming is also being practiced in other shipping markets.. In addition to being important from an economics perspective, speed reduction can also have important environmental benefits, as emissions from ships are directly proportional to fuel burned. In that sense, speed reduction is one of the important operational or logistics-based measures to reduce emissions from ships.. The purpose of this paper is to clarify some important issues as regards ship speed optimization at the operational level and to develop models that optimize ship speed for a spectrum of ship routing scenarios and for several variants that concern the objective function to be optimized. Its main contribution vis-a-vis the state of the art is the incorporation of those fundamental parameters and other considerations that weigh the most in a ship owner's or charterer's speed decision at the operational level and also in his routing decision, wherever relevant. These are (a) the fuel price, (b) the state of the market (freight rate), (c) the inventory cost of the cargo, and (d) the dependency of fuel consumption on payload. To do so, the paper goes over various examples so as to illustrate the properties of the optimal solution and the various trade-offs that are involved.. The rest of this paper is organized as follows. In section 2 we discuss modeling approaches for this class of problems, including assumptions, simplifications and possible misconceptions. In section 3 we list the scenarios and problem variants examined in the paper. In section 4 we discuss some properties of the optimal solution, including some that are counter-intuitive. Finally in section 5 we present the paper's conclusions. An Appendix describes the algorithm used for one of the examples in the paper. This paper has clarified some important issues as regards ship speed optimization and developed models that optimize ship speed for a spectrum of routing scenarios and for several variants that concern the objective function to be optimized. In our opinion, the main contribution of this paper vis-a-vis the state of the art is the incorporation of those fundamental parameters and other considerations that weigh the most in a ship owner's or charterer's speed decision at the operational level (and as it turns out, also the routing decision, wherever relevant). These are (a) the fuel price, (b) the state of the market (freight rate), (c) the inventory cost of the cargo, and (d) the dependency of fuel consumption on payload. To that effect, it can hopefully contribute to further research in this area, for instance in multiple ship problems where many of the properties identified in this paper are still valid.. The paper has confirmed that solutions for optimal environmental performance are not necessarily the same as those for optimal economic performance. Also policies that may seem at first glance optimal from an environmental viewpoint may actually be suboptimal. As a private operator would most certainly choose optimal economic performance as a criterion, if policy-makers want to influence the operator in his decision so as to achieve results that are good from a societal point of view, they could play with parameters that would internalize the external costs of CO 2 produced and move the solution closer to what is deemed more appropriate for the environment and for the benefit of society. For instance, imposing a tax on fuel would artificially increase fuel prices, induce slower steaming and further reduce emissions.. In the quest for a balanced economic and environmental performance of maritime transport, we think that this work can provide useful insights.

B I I O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Testing of the voice communication in smart home care This article is aimed to describe the method of testing the implementation of voice control over operating and technical functions of Smart Home Come. Custom control over operating and technical functions was implemented into a model of Smart Home that was equipped with KNX technology. A sociological survey focused on the needs of seniors has been carried out to justify the implementation of voice control into Smart Home Care. In the real environment of Smart Home Care, there are usually unwanted signals and additive noise that negatively affect the voice communication with the control system. This article describes the addition of a sophisticated system for filtering the additive background noise out of the voice communication with the control system. The additive noise significantly lowers the success of recognizing voice commands to control operating and technical functions of an intelligent building. Within the scope of the proposed application, a complex system based on fuzzy-neuron networks, specifically the ANFIS (Adaptive Neuro-Fuzzy Interference System) for adaptive suppression of unwanted background noises was created. The functionality of the designed system was evaluated both by subjective and by objective criteria (SSNR, DTW). Experimental results suggest that the studied system has the potential to refine the voice control of technical and operating functions of Smart Home Care even in a very noisy environment. Technologies that help seniors to live a quality life and to be more self-sufficient in everyday life are being developed. One of the fields of this development and innovation of modern technologies is Smart Home [1] to ensure independent living for senior citizens or disabled persons in household environment with the option of assistance care (Smart Home Care).. A sociological survey has been carried out to find out the needs of seniors [2] in the field of modern technology. The survey was aimed towards persons over 45 years old and thus also towards people that are not yet in senior age. The total number of respondents was 98. The goal of the survey was to find out what attitude towards modern technology not only seniors, but also middle-aged people preparing for retirement have. The survey shows that seniors use technology more and more. Prejudices and fears of new machines and devices fall. The survey was handed out in homes for the elderly, in nursing homes and to people living in private homes. Conditions that have often occurred in the survey replies for the use of modern technology in personal lives of seniors were as follows: "the need to understand modern technology, easy usability of the technology, usefulness of the technology for everyday life".. Many homes for the elderly in the Czech Republic are nowadays equipped with at least basic safety devices like cameras, smart cards registering the departure and arrival of inhabitants, fire detectors, alarms and so on. The vast majority of seniors are equipped with a mobile phone, especially for the feeling of their own safety and the possibility to contact quickly the person close to them. For the purpose of illustration, here are answers to some questions. Respondents answered the following question: "If I could to choose, I would like to live in" as follows:. 69 % of the respondents are satisfied with their current situation in terms of living and would not want to change it, 5 % of respondents would want to move from a home for the elderly or a nursing home to a private home, 4 people (4 %) would move to a home for the elderly in the future and 6 people (6 %) would move to a nursing home, 16 people (16 %) would live in an intelligent house.. To increase the safety inside residential premises, most of the respondents would use:. CCTV in common areas (64 %) A SOS button (56 %) Sensor equipment (smoke detectors, gas and water leakage detectors), (43 %) Medical equipment (check of physiological functions) along with Cameras in private areas scored the least points (13 % and 2 %). The respondents answered the question about the comfortable way to control operating and technical functions of Smart Home as follows:. 46 % of respondents still prefer manual control over the house/apartment 24 % of respondents would want to control Smart Home by voice 12 % of them would control it via a computer 8 % by touchscreen and 10 % of respondents would use it through portable devices Based on the preference of voice control over the operating and technical functions of Smart Home Care, a voice control system was designed to control the operating and technical functions in the real environment of Smart Home Care. This system was later presented inside the laboratories of VŠB-TU Ostrava on a model with implemented KNX technology (Fig. 6) .. In real-life implementations of the designed systems for voice communication [3] [4] [5] [6] with the control system it is necessary to resolve an issue with additive noises for the particular environment [7, 8] . Voice control in smart apartments is preferred mainly by older or handicapped fellow-citizens [9] . This paper focuses on the design and implementation of a comfortable voice control operational and technical functions in intelligent building with the KNX technology system. The whole work could be notionally divided into three parts, namely the development of applications for voice recognition, programming and animation has finished school model and implementation of a communication interface between these parts. The actual recognition of voice commands will be implemented on the platform. NET Framework 4.0 using C# programming language. Recognition results in machine code will be sent over UDP server using KNX / IP router from the host to the school model. After completing work on a model of intelligent building and a successful implementation of voice control is carried out functional and quality voice recognition testing.. The task of the designed software G.H.O.S.T for voice control of operational technical functions of a Smart House is to provide users with easy and simple access to control of their house. This application can serve as a complement to other technologies, supporting Tele Care in Smart Home Care. For example, for determining the position of the senior citizen's in Smart Home Care [10] . The aim of this work was to develop, implement and test voice control of operational and technical functions in a smart building. The final implementation was performed on a simulation model of a smart apartment. This model is able to simulate control of lighting, sun-blinds and air conditioning. Another task was to design a connection of the voice recognition system to the KNX bus and connection of the smart building simulation model. After performing an analysis of available and usable voice recognition systems, a set of criteria was established in order to enable the final implementation of the created system. The main criterion for the selection of the final solution was the price of the application. Use of the Microsoft SAPI module is free in the English version of the Windows system, however, an application to communicate with the KNX bus system on the user side and on the other side had to be created. A voice synthesis feature was implemented in the application. The final application is able to recognize not only the user's voice commands, but the application may also answer back. In order to test the functionality of the entire work, a statistics module was added to the application. To improve user comfort, a settings menu was added which enables the user to adjust the basic properties of the synthesis and voice recognition modules.. The next step in the development was the actual start-up and programming of the Smart Home Care simulation model. ETS software was used to program the KNX technology. Functionality was demonstrated by controlling lights and blinds. After the Smart Home Care module was successfully programmed, communication between this model and the created application was tested. A KNX/IP router was used to create communication between the KNX network and the personal computer. The advantage of this solution, as opposed to using a USB bus, is that it would be theoretically possible to connect/insert a Wi-Fi router between the KNX/IP router and the computer, and communicate with the entire network wirelessly. Communication was done via the Ethernet. The application was additionally programmed with a UDP client and a KNX/ IP router was integrated into the Smart Home Care simulation model. The Wire Shark program was used to obtain communication addresses, ports and to transmit messages. The most difficult part was the actual creation of the voice recognition application and establishing communication with the KNX bus. The designed and implemented solution works according to the requirements. The indisputable advantage is zero cost, provided that the user is running Windows Vista (or higher) in the English version. As evident from the success achieved by the proposed voice recognition communication method, the voice recognition feature works very well. Ten people participated in the testing. Each person conducted five tests and uttered 100 voice commands. The average success rate of real voice recognition based on all tests is approximately 98.78 % (note that interference, noise or greater distance between the speaker and the microphone were used during certain tests). Some minor errors occasionally occurred when the application was in idle mode (waiting for the activation phrase) and a conversation in Czech language was taking place in the room. This problem is eliminated by adding a restrictive conditions to the program, which accepts the initiation phrase if the application is at least 90 % sure that the phrase was correctly received/said. Despite this, the program may sometimes recognize a Czech word as the actual initiation phrase. As a possible improvement -when used in the real world, it is advisable to use a microphone network covering the entire area of the building.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Longitudinal

analysis

of

pain

in

patients

with

metastatic

prostate

cancer

using

natural

language

processing

of

medical

record

text

Objectives

To

test

the

feasibility

of

using

text

mining

to

depict

meaningfully

the

experience

of

pain

in

patients

with

metastatic

prostate

cancer,

to

identify

novel

pain

phenotypes,

and

to

propose

methods

for

longitudinal

visualization

of

pain

status.

Materials

and

methods

Text

from

clinical

encounters

for

men

enrolled

in

a

longitudinal

clinical/molecular

autopsy

study

of

metastatic

prostate

cancer

(Project

to

ELIminate

lethal

CANcer)

was

subjected

to

natural

language

processing

(NLP)

using

Unified

Medical

Language

System-based

terms.

A

four-tiered

pain

scale

was

developed,

and

logistic

regression

analysis

identified

factors

that

correlated

with

experience

of

severe

pain

during

each

month.

Pain

is

a

debilitating

part

of

the

experience

of

metastatic

cancer.

An

automated

system

to

categorize

and

track

pain

in

electronic

medical

records

could

provide

a

powerful

means

to

improve

clinical

care,

and

could

allow

novel

'high

pain'

or

'low

pain'

phenotypes

to

be

defined

and

studied

on

a

molecular

basis.

We

tested

the

feasibility

of

using

natural

language

processing

(NLP)

of

text

from

clinical

encounters

to

depict

meaningfully

the

experience

of

pain

in

patients

with

metastatic

prostate

cancer

over

time.

Electronic

health

records

have

greatly

facilitated

detection

and

understanding

of

disease

phenotypes

and

their

relationship

with

genetic

and

non-genetic

factors.

The

study

reported

here,

which

we

believe

to

be

the

first

to

use

NLP

to

obtain

longitudinal

pain

status

information

in

a

cohort

of

patients,

shows

that

NLP-based

monitoring

of

patient

pain

status

is

feasible

and

generalizable

to

new

datasets,

and

provides

a

number

of

phenotype-oriented

observations

useful

for

guiding

future

research.

Future

studies

should

focus

on

comparison

of

pain-status

tracking

by

NLP

versus

other

validated

pain

survey

tools,

and

on

practical

integration

of

the

two

methods

in

settings

where

electronic

health

records

are

in

routine

use.

Provenance

and

peer

review

Not

commissioned,

externally

peer

reviewed..

Open

Access

This

is

an

Open

Access

article

distributed

in

accordance

with

the

Creative

Commons

Attribution

Non

Commercial

(CC

BY-NC

license,

which

permits

others

to

distribute,

remix,

adapt,

build

upon

this

work

non-commercially,

and

license

their

derivative

works

on

different

terms,

provided

the

original

work

is

properly

cited

and

the

use

is

non-commercial.

See:

In

multivariate

regression

analysis,

pain

status

detected

by

NLP

correlated

statistically

with

parameters

clinically

known

to

be

associated

with

increased

pain.

Conversely,

pain

status

detected

by

NLP

was

not

associated

with

parameters

not

expected

to

be

clinically

associated

with

pain

status,

such

as

administration

of

definitive

radiation

with

curative

intent.

These

results

suggest

that

meaningful

NLP-based

pain

status

monitoring

is

feasible.

While

this

project

used

a

rule-based

NLP

system,

machinelearning-based

NLP

tools

should

be

tested

in

future

work..

Text

in

longitudinal

data

is

valuable

for

the

study

of

symptoms

such

as

pain,

where

the

clinical

unstructured

description

may

be

more

complete

than

it

is

in

structured

data.

NLP

techniques

convert

such

unstructured

data

into

structured

data,

which

is

typically

more

amenable

to

rigorous

analysis

and

display.

Relief

of

pain

is

essential

in

the

management

of

many

acute

and

chronic

diseases,

and

convenient

automated

monitoring

of

patient

pain

status

could

provide

a

valuable

new

tool

for

improving

quality

of

life

and

care.

Real-time,

easy-to-interpret

views

of

the

pain

status

history

of

an

individual

patient

or

a

group

of

patients,

as

shown

in

figure

and

online

appendix

figure

could

allow

busy

clinicians

to

identify

patients

most

in

need

of

increased

pain

management

intensity,

and

allow

researchers

to

perform

visual

and

quantitative

comparison

of

groups

of

subjects

participating

in

clinical

trials

of

novel

therapies

or

novel

clinical

interventions..

NLP-based

determination

of

pain

status

may

help

to

identify

clinically

significant

molecular

differences

between

prostate

cancers.

For

example,

a

study

of

the

molecular

differences

in

the

cancers

of

the

two

men

who

apparently

experienced

no

severe

pain

could

provide

important

clues

to

the

biological

determinants

of

severe

pain

in

metastatic

prostate

cancer.

Similarly,

the

trend

toward

increased

pain

experienced

by

the

five

African-Americans

compared

with

the

other

men

in

the

study

is

consistent

with

an

oncology

clinical

trial

which

found

that

African-American

men

were

more

likely

than

white

men

to

have

extensive

disease

and

bone

pain.

The

purpose

of

the

project

was

discovery

over

a

closed

dataset

and

a

study

of

feasibility.

To

evaluate

and

improve

the

performance

of

the

NLP

algorithm

on

the

dataset,

we

completed

multiple

rounds

of

SME

evaluation

(GSB

and

RJT).

Across

all

patient

encounters,

the

NLP

algorithm

identified

pain

mentions

(mean

pain

mentions

per

record)

and

drug

mentions.

Worldwide,

prostate

cancer

is

the

second

most

commonly

diagnosed

cancer

and

the

sixth

leading

cause

of

cancer

death

in

men.

In

the

past

decade,

significant

effort

has

been

made

to

better

understand

and

reduce

the

burden

of

pain

on

the

cancer

patient,

the

patient's

family,

caregivers,

and

society.

Pain

status

can

predict

survival

in

metastatic

prostate

cancer,

and

changes

in

pain

status

have

been

examined

as

a

surrogate

marker

of

effectiveness

of

new

therapies.

Several

validated

pain

survey

tools

have

been

proposed

for

routine

clinical

care.

NLP

has

been

used

to

quantify

associations

between

diseases,

conditions,

and

symptoms,

for

vocabulary

discovery,

and

for

cohort

construction.

NLP

applications

focusing

on

pain

in

clinical

records

have

successfully

detected

the

experience

of

pain

in

free

text

within

an

electronic

medical

record.

Some

studies

suggest

that,

in

some

scenarios,

NLP

of

medical

record

text

may

perform

better

than

patient-completed

surveys

in

detection

of

clinically

relevant

pain.

Although

pain

has

previously

been

normalized

and

classified

manually

for

purposes

of

statistical

correlations,

we

used

NLP

to

automatically

characterize

the

experience

of

pain

over

thousands

of

records.

To

our

knowledge,

this

is

the

first

study

to

combine

NLP,

date

resolution,

and

statistical

analysis

to

create

a

longitudinal

study

of

pain

in

the

clinical

record.

Our

system

normalized

each

mention

of

pain

in

longitudinal

clinical

records

by

severity

classification

and

number

of

days

before

death.

We

used

regression

modeling

techniques

to

analyze

both

the

newly

structured

data

and

the

existing

structured

data

to

search

for

phenotypic

correlations

with

pain

in

the

context

of

metastatic

prostate

cancer..

Pain

management

is

fundamental

to

effective

clinical

care,

and

significant

pain

is

a

consequence

of

the

disordered

biology

of

many

cancers.

This

study

tests

the

feasibility

of

automatically

tracking

patient

pain

over

time

using

NLP

of

clinical

record

text.

If

NLP-based

pain

tracking

is

feasible,

further

study

will

be

indicated

to

test

the

hypothesis

that

adoption

of

NLP-based

pain

tracking

within

electronic

health

record

systems

could

provide

significant

added

value

in

clinical

care

and

in

advancing

research

in

disease

phenotyping.

O O O O O O O B I I O B I I O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Trade deals and/or on-package coupons The selection of either a pull or a push price promotion has mainly been investigated in contexts where manufacturers offer deals to consumers at the time of purchase or offer trade deals to retailers. This paper extends this framework to where manufacturers can offer either trade deals or rebate-like promotions to consumers such as on-pack coupons that stimulate the first and second purchases or a combination of the two promotion vehicles. It is demonstrated that the decision to implement either of the three promotion options critically depends, among other factors, on the percentage of first-time buyers who redeem their coupons at the second purchase. Particularly, a necessary condition to simultaneously offer both a trade deal and coupons is to have a positive coupon redemption rate. When possible, manufacturers prefer on-pack coupons over trade deals to take advantage of slippage and to further increase the overall demand via coupon-induced repeat purchase. Manufacturers are more likely to take the lion's share of channel profits.Keywords: On-pack coupons, pull price promotions, push price promotions, trade deal $ We thank three anonymous reviewers for their helpful comments and suggestions. The issue of whether manufacturers should target their price promotions to their trade partners or final consumers is far from being resolved. Price promotions designed for trade partners such as retailers, also known as push price promotions, generally reduce the regular wholesale prices with the hope that channel partners can find it optimal to fully or partially pass on received price-cuts to consumers and stimulate retail sales, while price promotions targeted at final consumers, known as pull price promotions, directly offer price discounts or other monetary incentives to consumers, with the primary goals of attracting consumers to retail places and stimulating immediate sales. Typically, price promotions are viewed as instruments used by sellers to price discriminate between groups of consumers of varying price sensitivity (Narasimhan, 1984; Varian, 1980; Su et al., 2014) . The primary belief underlying this view is that what really matters for consumers is the effective price they pay, regardless of where price cuts may originate.. In this line, traditional economic literature has long considered that the choice between some forms of push and pull price promotions is a simple exercise that exclusively depends on the marketer's taste as both are expected to provide the same outcomes in terms of retail prices, quantities sold, and channel profits. Cash rebates and trade deals are believed to be two of such price promotions that manufacturers offer indifferently to consumers and retailers in the context of a bilateral monopoly for the same outcomes (Ault et al., 2000) . However, this simplistic view of push and pull price promotions as subsidies offered by manufacturers to retailers and consumers is not always theoretically and empirically supported. For instance, Busse et al. (2006) provides with an empirical evidence that the subsidy analogy does not hold in the automobile industry. The effective price consumers paid is lower when a manufacturer offers an identical cash-back to consumers than to retailers. In such an industry where cash rebates alone represent marketing expenses in excess of $3 billion per year (Bruce et al., 2006) , a misallocation of promotional budgets can seriously damage manufacturers' profits and consumer welfare. A few theoretical works have attempted to explain why manufacturers may prefer cash rebates to trade deals. Gerstner and Hess (1991a) find that manufacturers prefer consumer rebates when there is a strong positive association between willingness to pay and redemption costs. Gerstner and Hess (1991b) again claim that manufacturers primarily use cash rebates to motivate retail participation in promotions even when promotions do not discriminate among consumers with different reservation prices. Ault et al. (2000) examine the argument that cash rebates are manufacturers' first choice because retailers do not fully passed on trade discounts to consumers. They find that even when this argument does not hold, manufacturers could still prefer consumers rebate as trade deals allow retailers to accumulate low-price inventories. Martín-Herrán et al. (2010) focus on trade promotions that reward retailers for units effectively sold and offer an integrative framework that explains why in some contexts the subsidy analogy may work, and why in some others it may be irrelevant. Martín-Herrán et al.'s theory supports the view that choosing between trade deals and cash rebates critically depends on the consumer sensitivity to both regular and promotional prices. Particularly, manufacturers are better (worse) off offering trade deals (cash rebates) when consumers are more (less) sensitive to promotions than to regular prices. This theory also claims that the subsidy analogy holds only if consumers react identically to regular and promotional prices.. Departing from cash rebates, Kumar et al. (2004) also investigate the optimal choice between push and pull price promotions in a context where an exogenously sales expansion target is set. The push price promotion in this research is a trade discount offered to retailers, while coupons are used as pull price promotions. It is demonstrated that the manufacturer may choose either trade deals or coupons depending on coupon redemption rates and the equivalence ratio of price reduction to coupon face value.. Observe that previous research on the choice between pull price and push price promotions exclusively applies on consumer promotions such as cash rebates, shelf price discounts, and coupons that have the property that they offer discounts up front at the time of purchase (see also, Demirag et al. (2011) in the presence of competition). Theories developed for this type of price promotions are hardly generalizable to promotions that offer a discount after a purchase or at the time of a second purchase. As a matter of fact, Lu and Moorthy (2007) demonstrate that coupons designed to offer deals up front with the purchase and rebates that are redeemed after the purchase do not work the same way and offer different outcomes. Particularly, they find that rebates are efficient at surplus extraction, while coupons offer more fine-tuned control over who buys the products. There is therefore a need to further study the trade-offs between push and pull price promotions using promotions with various properties to deepen our understanding of the challenges marketers encounter in the planning of their price promotion programs.. In this paper, we develop a framework where a manufacturer in a bilateral monopoly context has the possibility of offering a trade deal or a rebate-like promotion or a combination of both at the same time. We call rebate-like promotions any promotional activities that require consumers to first purchase the product at the regular price and then benefit from a price discount for the next purchase. We particularly focus on what is known as on-package coupons (Chen et al., 2005; Dhar et al., 1996) where consumers are aware of the pledged discount and it is factored into their decisions to make the first purchase at the regular price. As a consequence, on-package coupons have the potential of directly influencing first and repeat purchases. Our current modeling effort does allow for price discrimination. Due to the slippage phenomenon, consumers who purchase the product in the first period may or may not redeem their coupons in the second period, depending on their price sensitivity, among other factors.. The current research answers the following three questions:. 1. What are the conditions under which manufacturers should exclusively offer either trade deals or on-package coupons or a combination of the two promotion types? 2. How does the coupon redemption rate impact on the manufacturers' profits and, consequently, the type of consumer promotions that manufacturers are more likely to implement? 3. How do push and pull price promotions affect the sharing of channel profits?. We hope the answers to the first two questions will expand our understanding of the use of pull and push price promotions and offer useful guidelines to marketing managers to effectively plan and implement these promotional vehicles. More particularly, our distinctive contribution is to show that rebate-like promotions such as on-pack coupons, which incite consumers to make a first purchase at the regular price and a second purchase at a discounted price, are different from instant rebates and peel-off coupons and that this difference should be acknowledged in the theories that deal with manufacturers' strategic choice between push and pull price promotions.. In addition, the answer to the third question will also enrich the debate over the impact of some promotional activities on the relative profitability of channel members. Manufacturers' increasing use of price promotions has been associated to a shift in the channel's economic power from the manufacturers to the retailers (Ailawadi, 2001; Nijs et al., 2001) . However, empirical and theoretical research on the relative profitability of channel members gives mixed results (Farris and Ailawadi, 1992 ; Martín-Herrán and Sigué, 2011; Messinger and Narasimhan, 1995; Sigué, 2008; Srinivasan et al., 2004) . In this research, we explore the idea that pull and push price promotions may have different impacts on the channel members' relative profits. As a matter of fact, during manufacturers' pull price promotions, such as coupons, retailers have the option of increasing their regular prices (Bruce et al., 2006; Busse et al., 2006; Gerstner and Hess, 1991a&b) . On the other hand, manufacturers fully rely on retailers to pass on to consumers the deals provided in push price promotions, which theoretically should give retailers additional leverage to increase their profits. It is not clear which of these two externalities benefits the retailers more, to the detriment of the manufacturers, in the case of trade deals and on-pack coupons.. The rest of the paper is organized as follows: First, we introduce two models: the Benchmark Model (BM) and the Full-Promotion Model (FM). Second, we derive the equilibria, identify the conditions under which the manufacturer may find it optimal to offer push and/or push price promotions, and compare the players' optimal profits in each scenario. Finally, we conclude by highlighting our contributions to advancing research and practice in this area.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I B I I B I I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O


A ultra low power CMOS pA/V transconductor and its application to wavelet filters Two topologies of ultra low-power CMOS triode transconductor are proposed. Its input transistors are kept in the triode region to benefit from the lowest g m /I D ratio. The g m is adjusted by a well defined (W/L) and V DS , the latter a replica of the tuning voltage V TUNE . Transconductance down to hundreds of pA/V are obtained and used to implement a 6th order wavelet filter. The resulting design complies with a 1.5V supply and a 0.35µm CMOS process. The total power consumption of the wavelet filters using the first and second topology of transconductor equals 51nW and 114nW, respectively. In the field of medical electronics, active filters with large time constants are often required to design low cutoff-frequency filters (in the Hz and sub-Hz range), demanding the use of large capacitors or very low transconductance. To limit capacitors to practicable values, a transconductor with an extremely small transconductance g m is needed. This paper presents two topologies of ultra low-power transconductor. Both configurations are compact and have their input transistors operating in the triode region to benefit from the lowest g m /I D ratio and linear variation of g m , which is controlled by an external voltage V TUNE . The advantages of this technique with respect to the techniques that employ voltage attenuation, source degeneration or current splitting [2] [3] [4] [5] can be found in [1] . The first g m , named VLPT-g m (very low-power triode g m ), with transconductance in the range of few nA/V. The second configuration, named Delta-g m , is presented here and the g m can be adjusted to values down to hundreds of pA/V. Subsequently, this paper presents an implementation of the wavelet transform with a Gaussian wavelet (gaus1) in an ultra low-power environment, using the proposed transconductors. Low-power analog realization of the continuous wavelet transform enables its application in vivo, e.g. in pacemakers and IECG recorders. Previous work on analog realization of the continuous wavelet transform uses the dynamic-translinear circuit technique [6] . Contrary to this approach, the g m is now controlled by voltage rather than by current. Translinear circuits become difficult to integrate when designing low cutoff-frequency filters for use in the Hz and sub-Hz range. As an example, for g m = 1nA/V, the VLPT-g m needs to be biased with a quiescent current around I Q = 300pA. To achieve the same time constant and considering the same bias current, the translinear circuit needs an increase of 12.6 times in capacitor value. Or, to maintain the same capacitor, it is necessary to decrease the current to 25pA, which is difficult to obtain precisely. Since (W/L) offers a degree of freedom in sizing g m , V DS values well above the equivalent noise of the biasing circuit can be set, while still obtaining a very-low g m . Consequently, filters with more predictable frequency characteristics can be implemented. Owing to its extended linearity, the triode-MOSFET transconductor also handles larger signals, with no need for linearization techniques. The paper organization is as follows. Section 2 introduces the triode transconductors circuits. Design procedures for realizing appropriate g m values and implementing the wavelet filter are discussed in Section 3. Simulation results are used to demonstrate circuit performance and tunability in Section 4. Conclusions and final remarks are given in Section 5. Two compact CMOS transconductors suitable for ultra-low power gm-C filters operating in the Hz and sub-Hz range have been proposed. Its input transistors are kept in the triode-region to benefit from the lowest g m /I D ratio. To validate the circuit principle, the transconductors were used to implement a wavelet transform with a Gaussian wavelet using a 6th order L 2 approximation.. The design was realized in accordance with VDD=1.5V and a 0.35µm n-well CMOS process. Simulation data were obtained with PSPICE and Bsim3v3 models. For the VLPT-g m, the transconductance ranges from 1nA/V to 12nA/V, total power consumption equals 51nW, for a total capacitance of 120pF. For Delta-gm filter, g m spans from 400pA/V to 4.8nA/V, with total power consumption of 114nW, for a total capacitance of 48pF. THD < 1% @200mVpeak_value was reached for every transconductor of the filters. The simulated step response of 6th order wavelet filter differs only slightly from the approximated response in both topologies. From this, we can conclude that the coefficients have been implemented successfully.

O O O O O B B O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Measures of semantic similarity and relatedness in the biomedical domain Measures of semantic similarity between concepts are widely used in Natural Language Processing. In this article, we show how six existing domain-independent measures can be adapted to the biomedical domain. These measures were originally based on WordNet, an English lexical database of concepts and relations. In this research, we adapt these measures to the SNOMED-CT Ò ontology of medical concepts. The measures include two path-based measures, and three measures that augment path-based measures with information content statistics from corpora. We also derive a context vector measure based on medical corpora that can be used as a measure of semantic relatedness. These six measures are evaluated against a newly created test bed of 30 medical concept pairs scored by three physicians and nine medical coders. We find that the medical coders and physicians differ in their ratings, and that the context vector measure correlates most closely with the physicians, while the path-based measures and one of the information content measures correlates most closely with the medical coders. We conclude that there is a role both for more flexible measures of relatedness based on information derived from corpora, as well as for measures that rely on existing ontological structures. Semantic relatedness refers to human judgments of the degree to which a given pair of concepts is related. Studies [1, 2] have shown that, surprisingly, most humans agree on the relative semantic relatedness of most pairs of concepts. Measures of relatedness are automatic techniques that attempt to imitate human judgments of relatedness. Many such techniques [3] [4] [5] [6] already exist in the realm of domainindependent Natural Language Processing. However, the lack of domain-specific coverage of the resources used by these measures makes them ineffective for use in domainspecific tasks. Because of the availability of numerous ontologies and resources in the biomedical domain, it is possible to adapt these measures and apply them to domain-specific tasks.. The existence of semantic equivalence classes between lexical items in English makes it highly desirable to use thesauri of synonymous or nearly synonymous terms for information retrieval (IR) and document retrieval (DR) applications. The issue is particularly acute in the medical domain due to stringent completeness requirements on such IR tasks as patient cohort identification. We believe that measures of semantic similarity and relatedness can improve the performance of such systems, since they are able to map a user's specific search query to multiple equivalent formulations. For example, a user's query for ''congestive heart failure'' could be expanded to include the semantically similar terms of cardiac decompensation, pulmonary edema, ischemic cardiomyopathy and volume overload. Clearly, pulmonary edema does not denote the same or even a similar disorder as congestive heart failure but under the patient cohort identification conditions it could be considered as an equivalent search term.. In this research, we adapt a number of measures of similarity and relatedness to the biomedical domain. We should emphasize that semantic relatedness and semantic similarity are two separate notions. Semantic relatedness is a more general notion of the relatedness of concepts, while similarity is a special case of relatedness that is tied to the likeness (in the shape or form) of the concepts. A measure of semantic similarity takes as input two concepts, and returns a numeric score that quantifies how much they are alike. Such a measure (e.g., [3] [4] [5] ) is usually based on isa relations found in the underlying taxonomy or ontology in which the concepts reside. For example, common cold and illness are similar in that a common cold is a kind of illness. Likewise, common cold and influenza are similar in that they are both kinds of illness. Of course, many ontologies include additional relations between concepts such as has-part, is-a-way-of-doing, is-a-cause-of, is-a-symptom-of, etc. that are not directly accounted for in measures of similarity. Thus, we view semantic similarity as a special case of semantic relatedness, and we believe that developing measures that take advantage of increasingly rich ontologies (particularly in the biomedical domain) which have a wealth of relations beyond is-a is an important area of future work. This is especially relevant in light of progress in automatically identifying a wide range of semantic relations in medical text (e.g., [7] ). We believe that the work in this article provides a necessary stepping stone to tackling the more general problem of identifying semantically related concepts.. Outside the biomedical domain, measures of semantic similarity and relatedness have proven useful in a number of NLP tasks. For example, Budanitsky and Hirst [8] identify malapropisms using various measures of similarity and relatedness. The premise of their approach is that a word that is not semantically similar or related to its neighbors may be a word that is misspelled but is accidentally a valid word, as in ''The nights of the round table rode again.'' Resnik [9] , Patwardhan et al. [10] , and McCarthy et al. [11] carry out word sense disambiguation based on the idea that a word should be used in the sense that is most similar to or related to the sense of the words that surround it.. However, all of this work has been domain-independent and has been based on WordNet [12] , which is a freely available lexical database that represents an ontology of approximately 100,000 general English concepts. In the biomedical domain, there are a growing number of ontologies that organize medical concepts into hierarchies and semantic networks, perhaps best exemplified by the Unified Medical Language System (UMLS Ò ) of the National Library of Medicine (NLM). One of the largest and most extensive sources included in UMLS Ò is SNOMED-CT Ò . To date, relatively little work has been done on developing and evaluating measures of conceptual similarity and relatedness for such resources. The premise of this article is that some of the measures that have been found to be effective with WordNet can be adapted and extended to SNOMED-CT Ò , thereby making it possible to automate certain NLP tasks in the biomedical domain.. This article starts by describing other related work in the biomedical domain as well as domain-independent techniques that implement or use measures of semantic similarity. The article then proceeds by introducing the various resources that we use in measuring similarity and relatedness among concepts. This includes SNOMED-CT Ò , the Mayo Clinic Corpus of Clinical Notes, and the Mayo Clinic Thesaurus. We then describe the five measures of similarity and one measure of relatedness (all based on WordNet) that we have adapted to the biomedical domain. 1 We also introduce a new test bed for the evaluation of measures of semantic similarity and relatedness in the biomedical domain. Finally, we present our experimental results, and suggestions for future work. In this article, we have shown the efficacy of adapting measures of semantic similarity and semantic relatedness measures developed for domain-independent English to a specialized subdomain of biomedicine represented by SNOMED-CT Ò . We have also shown that the ontology-independent Context Vector measure is at least as effective other ontology-dependent measures, provided that there is a large enough corpus of unlabeled training data available. This finding is important because developing specialized ontologies such as WordNet, SNOMED-CT Ò or UMLS Ò is a very labor intensive process. Also, there are some indications that manually constructed ontology may not fully reflect the reality of semantic relationships in the mind of a practicing physician. The vector based measure can help alleviate these problems in addition to the benefit of rapid adaptation to a new domain.. In the near future, we plan to extend the measures of relatedness to use the UMLS Ò as a source of the ontological relations for path-based measures, and to use the UMLS definitions for the context vector measure. We also would like to experiment with applications of semantic relatedness measures to NLP tasks such as word-sense discrimination, information retrieval and spelling correction, in the biomedical domain. In the biomedical domain, measures of semantic similarity based on ontologies were developed as early as 1989. Rada et al. [13] devised a ''semantic distance'' measure based on semantic networks. They used MeSH as their semantic network, which consists of biomedical terms organized in a hierarchy. Indeed, one of the measures described in this paper was inspired by this work. Taking a similar approach, Caviedes and Cimino [14] developed the CDist measure for finding path lengths in the UMLS hierarchy. Two of the measures we compare in this paper are path-based measures. Our work with these measures primarily differs in the ontology being used to compute the paths and the path-lengths between concepts.. Recently, Lord et al. [15] adapted WordNet-based measures of relatedness to the Gene Ontology [16] , which is a highly specialized ontology of the molecular functions and biological processes of gene products. The hierarchy also describes cellular components associated with gene products. In this work, they find that the semantic similarity of proteins based on the ontology has a high correlation with ''sequence similarity,'' a separate measure based on the protein sequences. Our work, in comparison, deals with more general biomedical concepts, and provides a more robust evaluation against a manually created data set.. In addition to adapting existing measures to the biomedical domain, there has been some work in creating new techniques for measuring the similarity of terms and concepts. Work by Wilbur and Yang [17] defines a strength metric which is used to retrieve relevant articles using lexical techniques. The metric uses the correlation between the occurrences of a term in documents with the subjects of the documents to define the strength of the term. This metric is used by the PubMed service to index and retrieve relevant biomedical documents. Research done by Spasic and Ananiadou [18] , defines a new similarity metric based on a variation of edit distance [19] applied at a word level. In short, the semantic similarity of two terms is the cost associated with converting one term to another, using insert, delete and replace operations on words (instead of letters). This method additionally uses the UMLS taxonomy to minimize the effect of word variants. It also varies the costs associated with the operations, based on the ''semantic load'' of the word being edited. For example, deleting a known term present in the UMLS has a higher cost than deleting a conjunction.. Later in this paper, we describe a measure based on context vectors-inspired by Schü tze's [20] method for word sense discrimination. This, in turn, is an adaptation of Latent Semantic Indexing [21] commonly used in Information Retrieval. Latent Semantic Indexing (LSI) and Latent Semantic Analysis (LSA) have been shown to be useful in the biomedical domain for indexing and retrieval of clinical records [22, 23] , for classifying medical events [24, 25] and for managing variations in medical terminology [26] . In our research, we use some LSA principles for the vectorbased measure.. In the realm of domain-independent Natural Language Processing, semantic similarity has been recently used in numerous tasks such as spelling correction [8] , word sense disambiguation [10, 27] , information extraction [28] and textual inference [29] . All of these applications show that semantic similarity and semantic relatedness have proven useful in a domain-independent setting.

O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O