Transcript hinv1
Two (Extreme) Stereotypes Gene-originated research Disease-originated research "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." Genespecific DB Many reasons to integrate! Diseasespecific DB Often off-line Individual pts' raw data Diversity of data Difficult to digitize Difficult to standardize Inter-diseae merger makes little sense/ incentive Needs: H-inv/ Dis Ed as an Initial Omnibus Port to Dis Info Starting from a gene/ pathway… Off-line Diseasespecific DB Diseasespecific DB Diseasespecific DB Hinv Multidisease port Diseasespecific DB Diseasespecific DB ① Text mining with curation ② Summary exp data (e.g. pooled samples?) ③ Link to dis-specific DB Diseasespecific DB Diseasespecific DB Needs: H-inv/ Dis Ed as an Additional Annotation Base Starting from each disease… ① Interpretation of identified candidate genes/ loci Diseasespecific DB ② G-G interaction ③ Selection of candidate genes/ markers ④ Acquisition of physical clones for functional assays ① (Unexpected) relationship with other phenotypes suggesting (i) shared pathways and/or (ii) shared lifestyle/ env factors ② Selection of candidate genes/ markers Diseasespecific DB Multidisease port Hinv Diseasespecific DB Diseasespecific DB 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: Dis→Genes →Best annotation in the world (strength/mission of main body) • Tools for: Dis→Genes →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 ① Disease-specific DB, focused to few diseases, but with in-depth info. ② Broad disease coverage, with a text-book level info (no patients' data) ③ Clinical info DB on few diseases, more clinical practiceoriented (incl. patients' data) ④ Expression profiling DB with insights in gene regulation network for tailor-made medicine ⑤ Probability-based disease gene info DB for gene mapping and for genotype-phenotype prediction in clinical medicine ⑥ Focusing on a particular cohort Eventually, all gene- and all human phenotype (incl. disease)- DBs will be combined seamlessly and in unity. 2/4/03 Strategic Meeting Agreement WG D1 WG D2 WG D3 WG D20 ③ Clin info DB ③ Clin info DB ③ Clin info DB ③ Clin info DB ⑤ Prob ⑤ Prob ⑤ Prob ⑤ Prob genotypephenotype genotypephenotype genotypephenotype genotypephenotype ⑥ SNP/MS ⑥ SNP/MS ⑥ SNP/MS Unidirectional data flow H-inv, Dis ed ④ Exp profile DB ④ Exp profile DB ④ Exp profile DB ⑥ SNP/MS ④ Exp profile DB ② H-inv version of Clinical Synopsis in OMIM based on automatic text mining with manual curation H-inv Publication Publication