1. 1 Data Integration and Extraction over Molecular Biological Data Cui Tao supported by NSF

2. 2 Motivation Online biological data: Highly diverse in granularity and variety Various formats Different terminologies, ID systems, units

3. 3 How to Build a Gene Extraction Ontology? Concepts Relationship sets Constraints Data Frames

4. 4 How to Build a Gene Extraction Ontology? (G*A*U*C*)* (G*A*T*C*)*

5. 5 Knowledge Sources Gene Ontology Thousands of terms All Species Toolkit 1,231,935 species names Protein Databases Thousands of protein names (Molecular Function, Biological Process,Molecular FunctionBiological Process, Cellular Component Cellular Component )

6. 6 Extraction Rules Statistical NLP Machine learning Naïve Bayes Hidden Markov Models Decision Trees

7. 7 Integration

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13. 13 Integration Information Hidden behind Links

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17. 17 Query-based Extraction Query the gene extraction ontology Find applicable resources Fill out forms Extract information

18. 18 Query-based Extraction Example: “Find the alfR gene, its sequence, its protein's function, and any mutant that inhibits this gene.” Gene Name Gene Sequence Gene Mutant Protein Function Mutant Function

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23. 23 Contribution Provides a way to automatically integrate online biological data from different sources Provides an approach that can find proper online resources, fill out online forms and extract data depending on user’s query