Gene- specific DB Disease- specific DB "I don't care other genes (pathways). Any disease welcome, as long as relevant to my gene (pathway)." "I don't care.

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Presentation transcript:

Gene- specific DB Disease- specific DB "I don't care other genes (pathways). Any disease welcome, as long as relevant to my gene (pathway)." "I don't care other diseases. Any gene welcome, as long as relevant to my disease." Gene-originated researchDisease-originated research Two (Extreme) Stereotypes Often off-line Individual pts' raw data Diversity of data Difficult to digitize Difficult to standardize Inter-diseae merger makes little sense/ incentive Many reasons to integrate!

H- inv Needs: H-inv/ Dis Ed as an Initial Omnibus Port to Dis Info Multi- disease port Disease- specific DB Disease- specific DB Disease- specific DB Disease- specific DB Disease- specific DB Disease- specific DB Disease- specific DB Starting from a gene/ pathway… Off-line Text mining with curation Summary exp data (e.g. pooled samples?) Link to dis-specific DB

Needs: H-inv/ Dis Ed as an Additional Annotation Base Disease- specific DB Disease- specific DB Disease- specific DB Disease- specific DB H- inv Starting from each disease… Multi- disease port Interpretation of identified candidate genes/ loci G-G interaction Selection of candidate genes/ markers Acquisition of physical clones for functional assays (Unexpected) relationship with other phenotypes suggesting (i) shared pathways and/or (ii) shared life- style/ env factors Selection of candidate genes/ markers

In Sum Strength of H-invitational DB, main body (my current understanding) –FL-nature –High-quolity sequences –Most comprehensive collection in the world –Availability of physical clones –Powerful computational and human resources –Integration with other genome-related databases To-do's for H-invitational DB, disease extension part (based on dis ed mtg) –Gene-originated/ oriented research Comprehensive and extensive automatic text mining with first-level manual curation for disease-related info Addition of disease-summary type wet data (e.g. exp profiling on pooled samples) Link with disease-specific DBs –Disease-originated/ oriented research Tools for: DisGenes Best annotation in the world (strength/mission of main body) Tools for: DisGenes Relationship with other phenotypes (other dis, life-style) Tools for candidate gene selection (strength/mission of main body and dis ed part)

Dr. Gojobori's Option Catalog Disease-specific DB, focused to few diseases, but with in-depth info. Broad disease coverage, with a text-book level info (no patients' data) Clinical info DB on few diseases, more clinical practice- oriented (incl. patients' data) Expression profiling DB with insights in gene regulation network for tailor-made medicine Probability-based disease gene info DB for gene mapping and for genotype-phenotype prediction in clinical medicine Focusing on a particular cohort Eventually, all gene- and all human phenotype (incl. disease)- DBs will be combined seamlessly and in unity.

H-inv H-inv version of Clinical Synopsis in OMIM based on automatic text mining with manual curation Exp profile DB SNP/MS Prob genotype- phenotype Clin info DB WG D1 Exp profile DB SNP/MS Prob genotype- phenotype Clin info DB WG D2 Exp profile DB SNP/MS Prob genotype- phenotype Clin info DB WG D3 Exp profile DB SNP/MS Prob genotype- phenotype Clin info DB WG D20 2/4/03 Strategic Meeting Agreement Uni- directional data flow Publication H-inv, Dis ed