Accomplishments and challenges in literature data mining for biology

• Published in: Bioinformatics 2002-12, Vol.18 (12), p.1553-1561
• Main Authors: Hirschman, Lynette, Park, Jong C., Tsujii, Junichi, Wong, Limsoon, Wu, Cathy H.
• Format: Article
• Language: English
• Subjects: Benchmarking - methods; Benchmarking - standards; Biological and medical sciences; Biology - methods; Computational Biology - methods; Database Management Systems; Databases, Bibliographic; Evaluation Studies as Topic; Fundamental and applied biological sciences. Psychology; General aspects; Information Storage and Retrieval - methods; Information Storage and Retrieval - trends; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Natural Language Processing; Online Systems; Quality Control
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/18.12.1553

We review recent results in literature data mining for biology and discuss the need and the steps for a challenge evaluation for this field. Literature data mining has progressed from simple recognition of terms to extraction of interaction relationships from complex sentences, and has broadened from recognition of protein interactions to a range of problems such as improving homology search, identifying cellular location, and so on. To encourage participation and accelerate progress in this expanding field, we propose creating challenge evaluations, and we describe two specific applications in this context. Contact: [e-mail] [e-mail] [e-mail] [e-mail] [e-mail] * To whom correspondence should be addressed.