Biomedical Literature Mining: Methods, Tools and Issues

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Biomedical Literature Mining Methods, Tools and
Issues

• Saurav Sahay

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Knowledge Explosion PubMed

• Average number of new citations appearing in
  PubMed
• In 1980 746/day
• In 2004 1,640/day

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Biomedical Text Mining Methods

• Databases
• Natural Language Processing
• Information Retrieval
• Information Extraction
• Ontologies
• Clustering
• Classification
• Visualization

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Gene Ontology
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Existing IR Systems
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Proposed System
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Some Open Problems

• Scalability of algorithms and databases
• mapping and interface of different data sources
• visual text mining to enhance productivity
• integration of different biomedical databases
• new measures of user effectiveness of system
• Full-text search and efficient indexing
• automatic updating of different ontologies
• borrowing ideas from bibliometric methods and
  digital libraries
• Summarizing and Question Answering

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References

• Amit Singhal, Modern Information Retrieval A
  brief overview, Google, Inc.
• Berry de Bruijn and Joel Martin. Getting to the
  (c)ore of knowledge mining biomedical literature
• Jonathan D. Wren. The emerging in-silico
  scientist how text-based bioinformatics is
  bridging biology and artificial intelligence
• L. Venkata Subramaniam, Sougata Mukherjea, Pankaj
  Kankar, Biplav Srivastava, Vishal S. Batra,
  Pasumarti V. Kamesam, Ravi Kothari. Information
  Extraction from Biomedical Literature
  Methodology, Evaluation and an Application
• Robert Mack and Michael Hehenberger. Text-based
  knowledge discovery search and mining of
  life-sciences documents
• Hans-Michael Müller, Eimear E. Kenny, Paul W.
  Sternberg Textpresso An Ontology-Based
  Information Retrieval and Extraction System for
  Biological Literature, PLOS Biology Volume 2,
  Issue 11, NOVEMBER 2004