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Automated Biomedical Information Extraction Tool for Researchers

Researchers in Biology and Medical Science often spend a significant amount of time scanning literature for information. PubMed/Medline, with around 12 million biomedical abstracts, is a vast resource. An automated system for information extraction would be highly beneficial. This tool aims to extract key information like gene interactions from bio medical abstracts using Biomedical Ontologies such as UMLS, GO, and LocusLink, utilizing a complex sentence processor and link grammar parser to identify interactions.

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Automated Biomedical Information Extraction Tool for Researchers

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  1. Information Extraction from BioMedical Abstracts Dr. Hasan Davulcu Syed Toufeeq Ahmed Deepthi Chidambaram

  2. Information Extraction from BioMedical Abstracts : Motivation • Researchers in Biology and Medical Science spend a large amount of time scanning the literature to get information. • PubMed/Medline (has around 12 million biomedical abstracts) is a tremendous source of biomedical knowledge in text form. • An automated system to extract the information would be very useful.

  3. Information Extraction : Goal “HMBA could inhibit the MEC-1 cell proliferation by down-regulation of PCNA expression.” { “HMBA”, “inhibit”, “the MEC-1 cell proliferation” } {“HMBA”, “down-regulation”, “PCNA expression”}

  4. Biomedical Ontologies UMLS, GO, LocusLink OVERVIEW Sentences (Abstracts) Complex Sentence Processor (Deepthi) Link Grammar Parser (Toufeeq) Simple Sentences with Linguistic Roles Interaction Extractor (Toufeeq) Extracted Gene/Gene Interactions

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