Biomedical Databases & Tools Rolando Garcia-Milian Biomedical & Health Information Services Department Health Sciences Center Library October 3, 2013
Problem – Rapid Growth of Biomedical data GenBank Statistics Compiled from GEO historic data
Compiled by from PubMed Biomedical Literature Problem – Growth of the Biomedical Literature Huge volume (PubMed citations) High diversity High quality (peer review) Users overwhelmed by long list of search results 1/3 of Pubmed queries result in 100 or more citations (Islamaj, 2009)
Querying the biomedical literature becomes more difficult Medical Subject Headings Filters Boolean operators Problem – Querying the Biomedical Literature
Alternative Mining Tools for the Biomedical Literature Main gene query Protein/gene associated Synonym Medical terminology
Based on Universal Medical Language System Repository of semantic predications (subject- predicate-object triples) 57.6 million predications from all of PubMed citations (Rindflesch, 2011) Alternative Mining Tools for the Biomedical Literature
Linked to Entrez Gene database
Workshop- Novel Online Tools for Mining the Biomedical Literature
Case 1 – Few Results in the Biomedical Literature Searching for novel genes
Case 2 – Few Results in the Biomedical Literature Searching for side effects of drugs: Cerebyx – respiratory failure
Phenotypic information can be used to infer molecular interactions and hinting at new uses of marketed drugs (Campillos, 2008) Case 2 – Few Results in the Biomedical Literature
Freely Available Up-To-Date Discovery Tools National Center for Biotechnology Information, USA European Bioinformatics Institute, UK
Proprietary Tools
Annotation/ Visualization Tools – Genome Browsers
Workshop- Introduction to Genome Browsers
References Campillos M*, Kuhn M*, Gavin AC, Jensen LJ, Bork P. Drug target identification using side-effect similarity. Science Jul 11;321(5886): Islamaj Dogan R, Murray GC, Névéol A, Lu Z. (2009) Understanding PubMed user search behavior. Database (Oxford) Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D. The human genome browser at UCSC. Genome Res Jun;12(6): Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P. A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol. 2010;6:343. Epub 2010 Jan Rindflesch, T.C. et al. (2011) Semantic MEDLINE: An advanced information management application for biomedicine. Information Services & Use, 31,
Data Resources Data Management Resources, UF Libraries: Surveys on Your Needs UF Research Data Needs Assessment: Big Data, Little Data Workshop Evaluation: