Biomedical Literature Mining [electronic resource] / edited by Vinod D. Kumar, Hannah Jane Tipney.

New York, NY : Springer New York : Imprint: Humana Press, 2014.
1 online resource (XII, 288 pages) : 51 illustrations, 36 illustrations in color.
Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 1159
Springer Protocols (Springer-12345)
Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 1159
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Life sciences.
Systems biology.
Computational biology.
Local subjects:
Life Sciences. (search)
Bioinformatics. (search)
Systems Biology. (search)
Computer Appl. in Life Sciences. (search)
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Biomedical Literature Mining,  discusses the multiple facets of modern biomedical literature mining and its many applications in genomics and systems biology. The volume is divided into three sections focusing on information retrieval, integrated text-mining approaches, and domain-specific mining methods. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.   Authoritative and practical, Biomedical Literature Mining  is  designed as a useful bioinformatics resource in biomedical literature text mining for both those long experienced in, or entirely new to, the field.
Introduction to Biomedical literature text mining: Context and Objectives
Accessing Biomedical Literature in the Current Information Landscape
Mapping of Biomedical Text to Concepts of Lexicons, Terminologies and Ontologies
Drug Interaction Text Mining
Biological Information Extraction and Co-occurence Analysis: State of the Art and Perspectives
Roles of Text Mining in Protein Function Prediction
Functional Molecular Units for Guiding Biomarker Panel Design
Mining Biological Networks from Full-text Articles
Scientific Collaboration Networks using Biomedical Text
Predicting future discoveries from current scientific literature
Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery
Integrating Literature and Data Mining to Rank Disease Candidate Genes
Role of Text Mining in Early Identification of Potential Drug Safety Issues
Systematic Drug Repositioning using Text Mining
Mining the Electronic Health Record for Disease-Specific Knowledge.
Kumar, Vinod D. editor.
Tipney, Hannah Jane. editor.
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10.1007/978-1-4939-0709-0 doi
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