# Presentation: 509370

## Semantic Network (SN) and Biomedical Ontology

- Barry Smith
- Department of Philosophy, University at Buffalo
- Institute for Formal Ontology and Medical Information Science
- ifomis.org

## Assumption

- 	SN is designed to support automatic reasoning involving multiple UMLS source terminologies
- Conclusion:
- 	Relations in SN are very important

## Inheritance

*Body part, Organ or Organ Component location_of Biologic Function*
- Therefore
*Body Part, Organ or Organ Component location_of Disease or Syndrome*
- Alexa: “We can *sometimes* infer ... you have to bring some medical knowledge to bear”

## Part_of as a relation between classes is more problematic than is standardly supposed

*testis part_of human being*  ?
- 	*heart part_of human being  *?

## Dr Humphreys: SN lists “possible significant relations”

## What we need for automatic inference is uniformly (necessarily) significant relations

*A is_a B*
*Every instance of A is an instance of B*

## What we need for automatic inference is uniformly (necessarily) significant relations

*A is_a B*
***Every**** instance of A is an instance of B*
- We hope all *is_a *relations are exceptionless in this sense

## Some non-is_a relations are exceptionless in this sense

*Fully formed anatomical structure ****contains ****body substance*

## But most are not

Bacterium causes Experimental Model of Disease
Experimental Model of Disease affects Fungus
Experimental model of disease is_a Pathologic Function

*Bacterium ****causes ****Experimental Model of Disease*
*Experimental Model of Disease ****affects**** Fungus*
*Experimental model of disease* ***is_a ****Pathologic Function*

## 
Bacterium causes Experimental Model of Disease

causes – Brings about a condition or an effect. Implied here is that an agent, such as for example, a pharmacologic substance or an organism, has brought about the effect. This includes induces, effects, evokes, and etiology.

*Bacterium ****causes ****Experimental Model of Disease*
***causes***** **– Brings about a condition or an effect. Implied here is that an agent, such as for example, a pharmacologic substance or an organism, has brought about the effect. This includes induces, effects, evokes, and etiology.

## GALEN: Vomitus contains carrot

Gene Ontology: Menopause part_of Death

HL7: Individual Allele is_a Act of Observation

**Gene Ontology:** *Menopause ****part_of**** Death*
**HL7: ***Individual Allele ****is_a**** Act of Observation*

## Thesis: Biomedical ontology integration

*	*will never be achieved through integration of *meanings *or *concepts *in people’s heads
*	*the problem is precisely that different user communities use *different concepts *

## Promise of evidence-based medicine in the genomics era:integrating biomedical terminologies with EHR data

- need facility for dealing with time and instances (particulars, actual cases)
- 	with this tumor here and now in this breast ...

## Move from associative relations between meanings to strictly defined relations between the entities themselves

- See:
- 	Smith, Ceusters, Klagges, Köhler, Kumar, Lomax, Mungall, Neuhaus, Rector, Rosse
- 	“**Relations in Biomedical Ontologies”**
*	**Genome Biology*, in press

## Clear instructions

- Fewer mistakes

## Key idea

- To define ontological relations like SN’s
- 	*part_of, contains, adjacent-to *
- we need also to take account of *instances *and *time*
**	****(= link to Electronic Health Record)**

## Kinds of relations

- <class, class>: *is_a*, *part_of*, ...
- <instance, class>: this explosion **instance_of **the class *explosion*
- <instance, instance>: Mary’s heart **part_of **Mary

## Kinds of relations

- <class, class>: *is_a*, *part_of*, ...
- <instance, class>: this explosion **instance_of **the class *explosion*
- <instance, instance>: Mary’s heart **part_of **Mary
- 	= **instance-level part_of**** **is a primitive (you can’t define everything, on pain of circularity)

## part_of

A part_of B =def.
	for all a and all t, 
	if a is an instance of A at time t,
	then there is some instance b of B 
	such that a is an instance-level part_of b at t

ALL-SOME STRUCTURE

*A part_of B *=def.
- 	for all ***a ***and all ***t, ***
*	*if ***a ***is an instance*** ***of *A *at time ***t***,
*	*then there is some instance ***b ***of *B *
*	*such that ***a ***is an **instance-level part_of** ***b ***at ***t***
***ALL-SOME STRUCTURE***

## part_of

A part_of B =def.
	for all a and all t, 
	if a is an instance of A at time t,
	then there is some instance b of B 
	such that a is an instance-level part_of b at t

ALL-SOME STRUCTURE

*A part_of B *=def.
- 	for **all** ***a ***and **all**** *****t, ***
*	*if ***a ***is an instance*** ***of *A *at time ***t***,
*	*then there is **some**** **instance ***b ***of *B *
*	*such that ***a ***is an **instance-level part_of** ***b ***at ***t***
***ALL-SOME STRUCTURE***

## testis part_of human being  - NO

human testis part_of human being - YES

human ovary part_of human being - YES

*human testis**** part_of ****human being - ***YES**
*human ovary ****part_of ****human being - ***YES**

## transformation_of

*mature RNA*** *****transformation_of ****pre-RNA*
*fetus ****transformation_of***** ***embryo*
*adult*** *****transformation_of ****child*

## transformation_of

*	**C*2* transformation_of C*1* =*def. any instance of *C*2 was at some earlier time an instance of *C*1

## Note the problem of inverses here

- Not every child becomes transformed into an adult

## The Granularity Gulf as an obstacle to reasoning

- most existing data-sources are of fixed, single granularity
- many (all?) clinical phenomena *cross* granularities

## embryological development

## tumor development

* **C *
*c ***at** *t*

*c ***at** *t*1

-      *C*1

## Advantages of the methodology of enforcing commonly accepted coherent definitions

- 	promote quality assurance (better coding)
- 	guarantee automatic reasoning across ontologies and across data at different granularities, from molecule to clinic
- 	yields direct connection to times and instances in EHR

## Automatic reasoning

- non-*is_a *relations are all-some relations
*A ****R ****B =*def for all instances ***a ***of *A *there is some instance ***b ***of *B *such that ***a r b***
- where ***r ***is some instance-level relation
- If you know *A ****R ****B, *and you know that ***a ***is an instance of *A*, then you ***know***** **that there is some instance ***b ***of *B*
- and **inheritance is unrestrained (exceptionless)**
- if you know *B ****R************ ****C *you can reason with this instance ***b ***to infer that there is some *C, *
- and so on

## Conclusions for SN

- Remove the merely ‘possibly significant relations’ (these are *less *than facts)
- Reform definitions (remove circularity)
- Remove those relations, such as *prevents *which cannot be given a coherent instance-based **all-some **definition
- Reform treatment of inverses

## prevents

**Definition:** Stops, hinders or eliminates an action or condition.**Inverse: **prevented_by
*	**contraception ****prevents**** pregnancy*
*	**pregnancy ****prevented_by**** contraception*

## Better treatment of prevention

*contraception *
*	****causes ***
***	******	****prevention_of_pregnancy*

## Reform treatment of inverses

*adjacent_to* – “Close to, near or abutting another physical unit with no other structure of the same kind intervening. This includes adjoins, abuts, is contiguous to, is juxtaposed, and is close to.”
- Inverse: *adjacent_to*

## Adjacent_to is not its own inverse

*nuclear membrane adjacent_to cytoplasm*
**BUT NOT:**
*cytoplasm adjacent_to nuclear membrane*
*ovary adjacent_to parietal pelvic peritoneum*
**BUT NOT:**
*parietal pelvic peritoneum adjacent_to ovary*

## Better treatment of inverses

- Use ***preceded_by ***
- not ***precedes**** *as primary relation
***preceded_by**** *supports inheritance
- (supports automatic reasoning)
*embryological development ****precedes ****birth *NOT EXCEPTIONLESS

## If NLM does not reform SN 

- 	in something like this way, then someone else will build a competitor to integrate the UMLS for purposes of automatic reasoning and integration across granularities

## http://ifomis.org

**http://ifomis.org**

**  ****The End**

**Human-Caused Phenomenon or Process (Environmental Effect of Humans):**
-  Phenomenon and Process put together

- Entity

- Event

- Activity

- Phenomenon or Process

- Physical Object

- Conceptual
- Entity

**UMLS Semantic Types**

**gene** *part_of* **cell component**
**fully formed anatomical structure**

## 			        		   							         				         	  conceptual
 		   		               entity

					idea or concept

				      functional concept

					   body system

-  		   		               entity
- 					idea or concept
- 				      functional concept
- 					   body system

## But:

***	******Gene or Genome***** is defined as: “A specific sequence ... of nucleotides along a molecule of DNA or RNA ...”**
**	****and **
**	****nucleotide sequence *****is_a *****conceptual entity **

## 			         entity		

		   physical             conceptual
 		   object		       entity

					idea or concept

				      functional concept

					   body system

- 		   physical             conceptual
-  		   object		       entity
- 					idea or concept
- 				      functional concept
- 					   body system

- confusion of
**entity **and
**concept**

## Functional Concept:

- Body system *is_a *Functional Concept.
- but:
- Concepts do not perform functions or have physical parts.

## This: 

**This:**** **

**is not a concept**** **

## UMLS-SN Semantic Relation

**produces****Definition:** Brings forth, generates or creates. **Inverse: **produced_by
*	*
*	**artificial insemination produces pregnancy*
- 	*pregnancy produced by artificial insemination*

## Definitions

*	**conceptual_part_of* – Conceptually a portion, division, or component of some larger whole.
- should not be circular

*part_of* – “Composes, with one or more other physical units, some larger whole. This includes component of, division of, portion of, fragment of, section of, and layer of.” Inverse: has-part
***contains***** – “Holds or is the receptacle for fluids or other substances. This includes is filled with, holds, and is occupied by.” Inverse: contained_in**
*consists_of* – “Is structurally made up of in whole or in part of some material or matter. This includes composed of, made of, and formed of.” Inverse: constitutes
*connected_to* – “Directly attached to another physical unit as tendons are connected to muscles. This includes attached to and anchored to.” Inverse: connected_to
*interconnects* – “Serves to link or join together two or more other physical units. This includes joins, links, conjoins, articulates, separates, and bridges.” Inverse: interconnected by
*branch_of* – “Arises from the division of. For example, the arborization of arteries.” Inverse: has_branch

*tributary_of* – “Merges with. For example, the confluence of veins.” Inverse: has_tributary
*ingrediant_of* – “Is a component of, as in a constituent of a preparation.”  Inverse: has_ingredient
***physically_related_to***** – “Related by virtue of some physical attribute or characteristic.” Inverse: physically_related_to**

- connected_to and connects not clearly defined
- ingrediant_of doesn’t fit

**temporally_related_to – (co-occurs_with; precedes):** The relevant definitions are as follows:
*precedes *– “Occurs earlier in time. This includes antedates, comes before, is in advance of, predates, and is prior to.” Inverse: follows
*co-occurs_with* – “Occurs at the same time as, together with, or jointly. This includes is co-incident with, is concurrent with, is contemporaneous with, accompanies, coexists with, and is concomitant with.” Inverse: co-occurs_with
*temporally_related_to* – “Related in time by preceding, co-occuring with, or following.” Inverse: temporally_related_to

- Too unspecific. KIF annotations?
**affects – (interacts_with; disrupts; prevents; complicates; manages; treats): **The relevant definitions are as follows:
***interacts_with*** – **“Acts, functions, or operates together with.” Inverse: interacts_with**
***disrupts***** – “Alters or influences an already existing condition, state, or situation. Produces a negative effect on.” Inverse: disrupted_by**
***prevents***** – “Stops, hinders or eliminates an action or condition.” Inverse: prevented_by**
***complicates***** – “Causes to become more severe or complex or results in adverse effects.” Inverse: complicated_by**
***manages***** – “Administers, or contributes to the care of an individual or group of individuals.” Inverse: managed_by**
***treats***** – “Applies a remedy with the object of effecting a cure or managing a condition.” Inverse: treated_by**
*affects* – “Produces a direct effect on. Implied here is the altering or influencing of an existing condition, state, situation, or entity. This includes has a role in, alters, influences, predisposes, catalyzes, stimulates, regulates, depresses, impedes, enhances, contributes to, leads to, and modifies.” Inverse: affected_by

- interacts_with need not be affects
**occurs_in – (process_of): **The relevant definitions are as follows:
*process_of* – “Action, function, or state of.” Inverse: has_process
*occurs_in* – “Takes place in or happens under given conditions, circumstances, or time periods, or in a given location or population. This includes appears in, transpires, comes about, is present in, and exists in.” Inverse: has_occurrence

- No reason why one is a subclass of the other
**brings_about – (produces, causes): **The relevant definitions are as follows:
*produces* – “Brings forth, generates or creates. This includes yields, secretes, emits, biosynthesizes, generates, releases, discharges, and creates.” Inverse: produced_by
*causes* – “Brings about a condition or an effect. Implied here is that an agent, such as for example, a pharmacologic substance or an organism, has brought about the effect. This includes induces, effects, evokes, and etiology.” Inverse: caused_by
*brings_about* – “Acts on or influences an entity.” Inverse: brought_about_by
**performs – (carries_out, practices, exhibits):** The relevant definitions are as follows:

*carries_out* – “Executes a function or performs a procedure or activity. This includes transacts, operates on, handles, and executes.” Inverse: carried_out_by
*practices* – “Performs habitually or customarily.” Inverse: practiced_by
*exhibits* – “Shows or demonstrates.” Inverse: exhibited_by
*performs* – “Executes, accomplishes, or achieves an activity.” Inverse: performed_by
- Difference between “performs” and “carries out” unclear

**functionally_related_to – (manifestation_of; affects; occurs_in; uses; indicates; result_of; brings_about; performs):** The relevant definitions are as follows:
*manifestation_of* – “That part of a phenomenon which is directly observable or concretely or visibly expressed, or which gives evidence to the underlying process. This includes expression of, display of, and exhibition of.” Inverse: has_manifestation
*uses* – “Employs in the carrying out of some activity. This includes applies, utilizes, employs, and avails.” Inverse: used_by
*indicates* – “Gives evidence for the presence at some time of an entity or process.” Inverse: indicated_by
*result_of* – “The condition, product, or state occurring as a consequence, effect, or conclusion of an activity or process. This includes product of, effect of, sequel of, outcome of, culmination of, and completion of.” Inverse: has_result
*functionally_related_to* – “Related by the carrying out of some function or activity. ” Inverse: functionally_related_to

**analyzes – (assesses_effect_of): **The relevant definitions are as follows:
*assesses_effect_of* – “Analyzes the influence or consequences of the function or action of.” Inverse: assessed_for_effect_by
*analyzes* – “Studies or examines using established quantitative or qualitative methods. ” Inverse: analyzed_by
- conceptually_related_to – (property_of; conceptual_part_of; evaluation_of; measures; diagnoses; issue_in; derivative_of; developmental_form_of; degree_of; measurement_of; method_of; analyzes): **The relevant definitions are as follows:**

*property_of* – “Characteristic of, or quality of.” Inverse: has_property
*conceptual_part_of* – “Conceptually a portion, division, or component of some larger whole.” Inverse: has_conceptual_part
*evaluation_of* – “Judgment of the value or degree of some attribute or process.” Inverse: has_evaluation
*measures* – “Ascertains or marks the dimensions, quantity, degree, or capacity of.” Inverse: measured_by
*diagnoses* – “Distinguishes or identifies the nature or characteristics of.” Inverse: diagnosed_by
*issue_in* – “Is an issue in or a point of discussion, study, debate, or dispute.” Inverse: has_issue
*derivative_of* – “In chemistry, a substance structurally related to another or that can be made from the other substance. This is used only for structural relationships. This does not include functional relationships such as metabolite of, by product of, nor analog of.” Inverse: has_derivative
*developmental_form_of* – “An earlier stage in the individual maturation of.” Inverse: has_developmental_form
*degree_of* – “The relative intensity of a process or the relative intensity or amount of a quality or attribute.” Inverse: has_degree
*measurement_of* – “The dimension, quantity, or capacity determined by measuring.” Inverse: has_measurement
*method_of* – “The manner and sequence of events in performing an act or procedure.” Inverse: has_method
*conceptually_related_to* – “Related by some abstract concept, thought, or idea.” Inverse: conceptually_related_to

**spatially_related_to – (location_of; adjacent_to; surrounds; traverses): **The relevant definitions are as follows:
*location_of* – “The position, site, or region of an entity or the site of a process.” Inverse: has_location
*adjacent_to* – “Close to, near or abutting another physical unit with no other structure of the same kind intervening. This includes adjoins, abuts, is contiguous to, is juxtaposed, and is close to.” Inverse: adjacent_to
***surrounds***** – “Establishes the boundaries for, or defines the limits of another physical structure. This includes limits, bounds, confines, encloses, and circumscribes.” Inverse: surrounded_by**
***traverses***** – “Crosses or extends across another physical structure or area. This includes crosses over and crosses through.” Inverse: traversed_by**
***spatially_related_to***** – “Related by place or region.” Inverse: spatially_related_to**
- associated_with – (physically_related_to, temporally_related_to, functionally_related_to, conceptually_related_to, spatially_related_to): **associated_with is defined as “has a significant or salient relationship to.” Inverse: associated_with**
**Discussion**
- The inclusion of the opposition *Chemical Viewed Structurally *and *Chemical Viewed*** ***Functionally* raises the suggestion that SN might be better interpreted as clas‐sifying not entities but rather the concepts we have of such entities. The concepts we use when referring to chemicals can after all be divided quite naturally un‐der these two headings. Then, however, the root nodes of SN should be not: *Entity* and *Event*,* *but rather: *Entity Concept *and *Event Concept*, and the latter should themselves be re-assigned to the position of daughters of a new root *Concept. *A restructuring along these lines would how‐ever in other ways conflict radically with  SN’s current architecture. Above all, it would con‐tradict the fact that *Idea or Concept* is already itself a subnode of *Conceptual Entity*. It would also contradict explicit statements to the effect that SN is ‘an upper-level ontology ... in which all concepts are given a consistent and semantically coherent representation’. [**7**]
**Conclusion**
- A number of proposals have been advanced to increase SN’s effectiveness as a terminology integration platform that can support enhanced reasoning and information retrieval. Thus [**8**] argues that UMLS lacks the requisite granularity, semantic types and relationships for comprehensively and consistently representing anatomical concepts in machine readable form. [**9**] and  [**10**] propose enhancing the efficiency of UMLS-based reasoning systems via a clustering of SN nodes to yield more coarse-grained partitions of the network.
- Our proposal is that SN’s power to support terminology-based reasoning can be enhanced through a reclassification along the lines sketched in the above. As an example of how such a reclassification would support inferences currently blocked, consider the way in which SN currently views tissues and cells as *physical *parts of organs, but views these organs themselves as mere *conceptual parts *of body systems, which are in turn *conceptual parts *of fully-formed anatomical structures, which are in turn *physical *parts of organisms. When we reclassify *Body System *as a *Physical Entity*, there is no longer a need for the distinction between  conceptual and physical* part-of *relations*. *Reasoning systems can thus exploit the full power of mereology, including the rules governing transitivity of *part-of*.