Conferencia presentada por el Ing. José López, como parte del X Coloquio Internacional de Tecnologías aplicadas a los Serivicios de Información

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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 documentation
An application case: Apoptosis
“ X Coloquio internacional sobre tecnologías
aplicadas a los servicios de información”
UNET, November 2010
Universidad Nacional Experimental del Tachira
Decanato 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.
Synthesis
Apoptosis

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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.
Ontology
Reasoner
WebApplication
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
1
Biomedical Sciences Research Institute , University of Ulster,
Coleraine, Co. Londonderry, NI, UK .
2
Laboratorio de Computación de Alto Rendimiento, Universidad del Táchira,
San Cristóbal, Edo. Táchira, Venezuela
3
Research 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
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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 repository
To 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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References
1 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?