Development Information Extraction Tool: Toward
Construction of Protein-Protein Interaction Database

12

Tomoko Okazaki-Ohta1 2

Toshihisa Takagi1

okap@ims.u-tokyo.ac.jp

takagi@ims.u-tokyo.ac.jp

Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
JSPS Research Associate of JSPS Research Pro ject for the Future

1 Introduction
In connection with the development of the molecular biology in recent years, the amount of informationin genome area has been growing rapidly. Although many data about biomolecular structures havebeen comprehensively compiled into public databases, most of data as biological functions such as
molecular interactions are still only in the biological papers. Reading every articles in the world
requires too much time and labor. An interesting information extracting system is needed [1, 2].
Since there are many descriptions of various research backgrounds and hypotheses in papers, in order
to extract a certain knowledge and to build the database, the logical structure of a paper needs
to be understood and the sentence suitable for information extraction needs to be speci ed. Since
there is structure decided as the paper to some extent, while understanding the structure of the wholepaper, understanding the structure of the sentence expressing knowledge is connected with information
extraction. We propose here a technique of specifying the sentence which has the description of aprotein-protein interaction using the gure legend having shown the experiment result (Fig. 1).

POS
Tagging

HeuristicandDictionary

TaggerKnowledge Base

Sentence
Selection

Protein name
Prediction

Information
Extraction

Linguistic
PatternFigure 1: Overall Architecture.

2 Overview
The titles and abstracts of biological papers are compiled in MEDLINE database. However, these
are inadequate to extract the knowledge like protein-protein interaction. So we digitized the papers
relevant to protein-protein interaction by OCR, and created the full text database. At rst, gure292

legends were searched using keywords such as an experimental method, to specify the sentence which
is describing the fact checked by the experiment, except for the research background and hypothesis.
And, the sentence containing the number of the gure having the searched gure legend was takenfrom the result section. Then, the sentence containing the information on a target was narrowed
down. We have developed the tool which helps a man in reading such selected sentence and extracting
knowledge.
Our nal purpose is to extract the knowledge written in papers and to create the entry of adatabase automatically, and it is a target to automate the shaded portion which was shown in Fig. 1.
Full Text
Synonym Dictionary
Full Text DB

Title
Abstruct

Title:

SH2 : Src homology 2
PDGF : platelet-delieved growth factor
PI3K : phosphatidylinositol 3-kinaseAbstruct:

Introduction
Introduction:

Results

Discussion

OCR

Results:
Discussion:

Knowledge Base

Figure ledends:

Material & Methods

References

Figure 2 shows that similar amounts of HGF/
SF receptor were co-immunoprecipitatedfrom GTL-16 cells lysates with PLC-,
pp60 c-src , and the GRB-2-SOS complex
using the respective antibodies.

ID: 00001
Protein: HGF/SF receptor
Protein: PLCExperiment: coimmunoprecipitation
Comment : HGF/SF receptor have amultifunctional docking
site made of theReference : 00001

Figure 2: Information Extraction.

Acknowledgments
This work is partially supported by Grant-in-Aid for Scienti c Research on Priority Areas, \GenomeScience" from the Ministry of Education, Science, Sports, and Culture, Japan.

References[1] Fukuda, K., Tsunoda, T., Tamura, A., and Takagi, T., Toward Information Extraction: Identifying protein names from biological papers, Proc. of the Paci c Symposium on Biocomputing '98(PSB'98), 707-718, 1998
[2] Ohta,Y., Yamamoto,Y., Okazaki,T., Uchiyama,I., and Takagi,T., Automatic Construction ofKnowledge Base from Biological Papers, Proc. of the Fifth International Conference on Intelligent Systems for Molecular Biology (ISMB'97), 218-225, 1997

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