An Ontology for Protein- Protein Interaction Data Karen Jantz CIS Honors Project December 7, 2006

Overview  Problem Statement  Objectives  Approach  Background  Methodology  Evaluation  Demonstration  Conclusion

Problem Statement  Several sources for protein-protein interaction data  Different schemata  Different purposes  Different strengths/weaknesses

Objectives  Unify the data  Enable data mining  Evaluate reliability of data across data sources  Gain new information about the entire data set  Enable others to easily add other data sources to the set

Approach: ontology o ontology – n. 1. that which exists (philosophy) 2. that which is represented (artificial intelligence) o A descriptive data model o Defines the entities and relationships within a domain o Based upon data o Human-readable

Approach: ontology Data integration Enables simultaneous querying across multiple databases  Data transformation Enables interchange between database formats  Data mining Enables reasoning and learning over the entire data set

Background: Data Sources  DIP (Jing Xia) D atabase of I nteracting P roteins Most reliable data set Jing Xia  BIND (Abhijit Erande, Aaron Schoenhofer) B iomolecular I nteractions N etwork D atabank Very large data set Contains interactions, molecular complexes, and pathways

Background: Data Sources  MINT M olecular INT eractions database experimentally verified protein interactions Evaluates confidence level  IntAct Not limited to binary interactions Allows user submissions  mips CYGD M unich I nformation C enter for P rotein S equences: C omprehensive Y east G enome D atabase Limited to yeast Focuses on sequencing

Background: Tools  Protégé Open-Source Project Graphical ontology editor Interacts with OWL Reasoner Detailed API for modifying ontologies programmatically

Background: Tools  Prompt A Protégé Plugin Enables ontology mapping Enables ontology comparison

Background: Related Work  PSI-MI Controlled vocabulary for PPI data Not a proposed database structure Decreases the strength of information Helpful in defining relationships and keys

Methodology: Overview Q: What interactions have been observed between with protein A? DIPBINDMIPSMINTIntAct Web Interface Unified Ontology Unified Data Set Q: What experiments give evidence for a given interaction?

Methodology: Design  Review the singular database schemata and determine strengths/weaknesses  View data files Native formats PSI-MI formats  Create a unified schema of the data sources  Create the unified ontology in Protégé  Create each singular database as a subset of the unified ontology

Protégé Screenshot

Methodology: Data Import  DOMParser Load data from XML  Protégé-OWL API Insert entities into singular databases

Methodology: Transformation  Use Prompt to create a mapping for each specific data source to the unified ontology  Use Prompt mappings to insert individuals from each singular ontology into the unified model

Methodology: Transformation  Duplicate Data Need to fill in attributes on existing records Write ‘Algorithm Plugin’ for Prompt to determine when individuals are the same

Prompt Screenshot - Mapping

Methodology: Query Interface  Export Protégé data into MySQL  Web interface for collecting data  Working with domain experts to determine useful views, queries

Evaluation  Performance Transformation Time in Protégé Query Time for Web Interface  Size Minimize redundancy in data model Minimize duplicate data

Evaluation  Correctness Domain Experts  Dr. Brown, Dr. Wang Maintain proper data relationships  Utility Enrich data

Evaluation

Demonstration

Future Work  Complete transformations  Import data  Evaluate ontology  Add other databases to model

Conclusions  Adequate start  Needs improvement, evolution, more data sources  As the project matures, the ontology will be ready for use in the biological domain  Will be able to more easily gain information about protein-protein interactions

References  AAAI.org - AITopics: “Ontology”  Protégé owl.html owl.html  Prompt  PSI-MI

References  BIND  DIP  IntAct  MINT  MIPS

Q & A