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Advanced Literature-Mining Tools

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Bioinformatics

Abstract

The complexity and wide range of current biomedical research is reflected in the number and scope of biomedical publications. Due to this abundance scientists are often no longer capable of keeping up with publications in their specific areas of research, let alone finding, reading, and analyzing potentially related scientific publications. Real advances in research, however, can be achieved only if a researcher can obtain an overview of the state of a given research question in a timely manner. This chapter presents methods to help researchers access the content of the biomedical literature. Information Retrieval (IR) identifies, in a large document database, the documents that are most relevant to a search topic provided by a user. Natural Language Processing (NLP) affords finer-grained access to more precise information contained in texts, which opens up a range of data analysis and knowledge synthesis functionalities. Powerful tools have been designed to exploit these techniques for the benefit of biomedical researchers, extracting millions of facts from the published literature and assisting Literature-Based Discovery. This chapter is organized as follows. It first describes the current capacities of IR from the Medline® bibliographic database. A short introduction to the main concepts of Natural Language Processing follows. Tasks which build on Natural Language Processing are then presented: Information Extraction and its derivatives and Literature-Based Discovery. A review of some existing applications closes the chapter. The references cited in the text are supplemented by a list of textbooks and Web resources.

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Notes

  1. 1.

    http://lucene.apache.org/

  2. 2.

    http://www.ncbi.nlm.nih.gov/sites/entrez?db = pubmed

  3. 3.

    http://www.ncbi.nlm.nih.gov/entrez/query/static/eutils_help.html

  4. 4.

    http://vivisimo.com/

  5. 5.

    The complete term here is monoostotic fibrous dysplasia, and was obtained through the analysis of adjective coordination in a noun phrase.

  6. 6.

    MetaMap 2008 expands the abbreviation within the span of submitted text

  7. 7.

    Although these may actually be hypotheses, observations, results, etc., we refer to them uniformly as “facts.”

  8. 8.

    EbiMed – http://www.ebi.ac.uk/Rebholz-srv/ebimed/index.jsp

  9. 9.

    iHOP – http://www.ihop-net.org/

  10. 10.

    Chilibot – http://www.chilibot.net/

  11. 11.

    ARROWSMITH – http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/start.cgi

  12. 12.

    BITOLA – http://www.mf.uni-lj.si/bitola/

  13. 13.

    Semantic MEDLINE – http://skr3.nlm.nih.gov/SemMedDemo/

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Author information

Authors and Affiliations

  1. LIMSI-CNRS, Orsay, France

    Pierre Zweigenbaum

Authors
  1. Pierre Zweigenbaum
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  2. Dina Demner-Fushman
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Corresponding author

Correspondence to Pierre Zweigenbaum .

Editor information

Editors and Affiliations

  1. Inst. Molecular Bioscience, University of Queensland, St.Lucia, 4072, Australia

    David Edwards

  2. Dept. Plant & Microbial Biology, University of California, Berkeley, Koshland Hall 111, Berkeley, 94720, U.S.A.

    Jason Stajich

  3. e-Health Research Centre, Adelaide St. 300, Brisbane, 4000, Australia

    David Hansen

Appendices

Appendix

Lists of Tools and Services

State of the art NLP tools:

http://aclweb.org/aclwiki/index.php?title=State_of_the_art

Resource list compiled by Kevin Bretonell Cohen

http://compbio.uchsc.edu/corpora/bcresources.html

Resource list compiled by Robert Futrelle:

http://www.bionlp.org/

BioCreAtIvE bio-NLP tools:

http://biocreative.sourceforge.net/bionlp_tools_links.html

NLP and Text Mining Research list at NaCTeM:

http://www.nactem.ac.uk/research.php?view=4

Arrowsmith:

http://arrowsmith.psych.uic.edu/arrowsmith_uic/tools.html

The Open Directory Project:

http://www.dmoz.org/Science/Biology/Bioinformatics/Software/

The National Centers for Biomedical Computing (NCBC) funded under the NIH Roadmap for Bioinformatics and Computational Biology:

http://www.ncbcs.org/

Gene and Protein Name Resources

Entrez Gene:

http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene

FlyBase:

http://flybase.org/

HUGO Gene:

http://www.genenames.org/index.html

Model organisms:

http://www.nih.gov/science/models/

Mouse Genome Informatics:

http://www.informatics.jax.org/

Saccharomyces genome database:

http://www.yeastgenome.org/gene_list.shtml

The Worldwide Protein Data Bank:

http://www.wwpdb.org/

UniProt:

http://www.ebi.ac.uk/uniprot/

Biomedical Terminologies

The national center for biomedical ontology:

http://bioontology.org/

The open biomedical ontologies:

http://www.obofoundry.org/

Resources for Biomedical Terminology and Ontology:

http://www.ldc.upenn.edu/mamandel/itre/term.html#Dictionaries

Unified Medical Language System

http://www.nlm.nih.gov/research/umls/

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Zweigenbaum, P., Demner-Fushman, D. (2009). Advanced Literature-Mining Tools. In: Edwards, D., Stajich, J., Hansen, D. (eds) Bioinformatics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-92738-1_17

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