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José López <jlopez@unet.edu.ve>

Jacinto Dávila <jacinto@ula.ve>

Dahyana Nimo <dahycar@gmail.com>

Mary Carlota Bernal <marybernalj@gmail.com>

Javier Maldonado <jamc2004@gmail.com>

An approach to integrate ontologies, NLP and Web Services to analyze

scientific documentationAn application case: Apoptosis

“ X Coloquio internacional sobre tecnologías aplicadas a los servicios de información”

UNET, November 2010

Universidad Nacional Experimental del TachiraDecanato de Investigación

Laboratorio de Computación de Alto Rendimiento-LCAR

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Agenda

• The apoptosis signaling network (the application case)

• Extending an ontology.

• Queries (types of).

• Building the ontology.

• What we search to reason about?

• A proposal for an intelligent web system based on ontologies, NLP and Web Services

• A first set of conclusions.

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To develop a web system able to deal with queries searching for possible relationships and interactions in the Apoptosis network map.

But also...

A platform able to support generic bio-molecular knowledge analysis from specialized documentation

Motivation

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Apoptosis... ... or how a cell dies.

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The Apoptosis signaling network

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•It is often difficult to keep in mind all of the known interactions

•Molecular interaction maps can suggest new interpretations or questions for experiment.

•The act of preparing a molecular interaction map imposes a discipline of logic and critique to the formulation of functional models

•A diagram convention provides a shorthand for recording complicated findings or hypotheses.Kurt W. Kohn, Molecular Interaction Map of the Mammalian Cell Cycle Control and DNA Repair Systems, Mol. Biol. Cell, Vol. 10, Issue 8, 2703-2734, August 1999

Why is useful a Molecular Interaction Map?

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Queries guiding the BioPAX ontology extension

Given a ligand, what type of protein-protein interactions result when it binds to a cognate receptor, and which of them lead to the up-regulation of a transcriptional response?

Given a DNA motif, its related receptor(s) and (or) complex(es), which genes are transcriptional up-regulated or down-regulated by?

Given a receptor and its associated complex(es), in which tissues are they related with a high (or low) transcriptional response for its targeted genes?.

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Adapting the BioPAX ontology … …. to represent the Apoptosis signalling network.

The BioPAX Ontology (Local extended version)

Synthesis

isa

Multiple organism-tissue specificities for protein or pathway descriptions.

ACTIVATION-TRANSCRIPTIONAL

STIMULATION-TRANSCRIPTIONAL

INHIBITION-COMPETITIVE-TRANSCRIPTIONAL

ACTIVATION- RECEPTOR

INHIBITION-RECEPTOR

Synthesis

To model DNA->Protein events and related pathway steps.

SynthesisApoptosis

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Building the Apoptosis digital representation using the BIOPAX ontology (Local extended version)

Protein instances

Description for a particular complex

A set of entities representing a partial view of the Apoptosis SN

Here a partial Apoptosis SN list of complexes.

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Building the Human Reactome

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A first web application prototype to reason about a SN ontology

Queries

Answers(Relations).

MIM uploading/downloading

XML data base

Web System

HTML based user interface

1

1. Consults to the reasoner to get answers for queries

2. Reasoner’s results to format as answers

3. BioPAX-vE Knowledge base updates and consults

4. Reasoner access to a particular BioPAX-vE file.

OntologyReasoner

Web

App

licat

ion

BioPAX-vE OWL Files

2

3

BioPAX-vE: BioPAX version Extended

4

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A standard-compliant global map of the bile acid/xenobiotic signaling network:

Construction and automated query processing.

O. Schmidt1, J. López2, F. Azuaje3, P. Thompson1, M. Swain1, and W. Dubitzky1

BIOCOMP'09

The 2009 International Conference on Bioinformatics & Computational Biology

Monte Carlo Resort, Las Vegas, Nevada, USA (July 13-16, 2009)

A first goal

1Biomedical Sciences Research Institute , University of Ulster, Coleraine, Co. Londonderry, NI, UK .

2Laboratorio de Computación de Alto Rendimiento, Universidad del Táchira, San Cristóbal, Edo. Táchira, Venezuela

3Research Centre for Public Health (CRP-Santé), Cardiovascular Research Strassen, Luxembourg

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How to reason about a signalling network?

Knowledge Base

Reasoner(Inference Engine)

A MIM related query

Explanations, Planning and Predictions

An Explanation:

A prediction:

Given A is possible p?

A plan:To obtain p which A I have to follow?

Given O which A is related with?

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An intelligent web system to represent and reason about a signaling network

MIM Ontology Edition?MIM Local XML Edition?MIM SBML Edition?

Queries

Explanations, Planning and Predictions.

MIM uploading/downloading

XML, OWL data base

Web server

User interface

1

1. Digital representation management

2. Knowledge base building and management

3. knowledge base delivering and monitoring

4. Knowledge base consults and updates

5. Reasoner answers

6. Access to repositories of models

7. Web services based access to models and KBs

22

3

4

4

5

6

6

Models and KBs repository

KB Builder/Monitor

Reasoner

7

6

Reasoner

Knowledge Base

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An architecture for a summarizer

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(Subject, Relation, Object)Producer

Ontology Translation

Ontologies

Automatic Ontology Annotation

To ontologies repositoryTo general purpose KB

KB Builder

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An adapted dictionary for MIM analysis

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The kind of output from the summarizer

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Conclusions (…at this time)

• The Ontologies defines a format for qualitative analysis and information sharing.

• The ontology used imposes an organized and detailed description about the knowledge domain.

• The manual annotation must be supported by some kind of automatic process.

• The summarizer has been connected with a knowledge domain using the ontology producing relevant summaries.

• An approach to deal with general logic analysis and automatic ontology annotation had been proposed.

• A standard procedure must be implemented to connect the architecture proposed with relevant APIs and Web Services.

• A similar approach coul be followed with other knowledge domains using ontologies and other methods to produce specialized lexical.

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References1 Metabolism - Basic introduction to metabolism. The Virtual Library of Biochemistry, Moleculer Biology and Cell Biology.

http://www.biochemweb.org/.

2 Timothy T. Lu, Makoto Makishima, Joyce J. Repa, Kristina Schoonjans, Thomas A. Kerr, Johan Auwerx, and David J. Mangelsdorf. Molecular Basis for Feedback Regulation of Bile Acid Synthesis by Nuclear Receptors. Molecular Cell, Vol. 6, 507–515, September, 2000.

3 Molecular Interaction Maps. The Genomics and Bioinformatics Group. http://discover.nci.nih.gov/mim/index.jsp

4 Kurt W. Kohn, Molecular Interaction Map of the Mammalian Cell Cycle Control and DNA Repair Systems, Mol. Biol. Cell, Vol. 10, Issue 8, 2703-2734, August 1999.

5 Hiroaki Kitano, Akira Funahashi, Yukiko Matsuoka1, Kanae Oda. Using process diagrams for the graphical representation of biological networks, Nature Biotechnology 23(8), 961 - 966 (2005).

6 Systems Biology Markup Language (SBML) Level 2: Structures and Facilities for Model Definitions, 2003. http://sbml.org/documents/.

7 BioPAX – Biological Pathways Exchange Language. Level 2, Version 1.0 Documentation, 2005. http://www.biopax.org/

8 CellDesigner.org. http://www.celldesigner.org/

9 Protégé. The de facto standard for editing OWL. http://protege.stanford.edu/

10 Catherine M. Lloyd et al; CellML its future, present and past; Progress in Biophysics & Molecular Biology 85 (2004) 433–450.

11 Baral et al; A knowledge based approach for representing and reasoning about signaling networks;Bioinformatics, Vol. 20 Suppl. 1 2004, pages 115–122.

12 Mindswap: Maryland Information and Network Dynamics Lab Semantic Web Agents Project http://www.mindswap.org/2003/pellet/index.shtml

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Questions?