Biomedical Literature Mining

1. Front Matter

   Pages i-xii

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2. Introduction to Biomedical Literature Text Mining: Context and Objectives

   • Jeffrey D. Saffer, Vicki L. Burnett

   Pages 1-7

3. Principles of Text Mining: Getting Started

   1. Front Matter

      Pages 9-9

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   2. Accessing Biomedical Literature in the Current Information Landscape

      • Ritu Khare, Robert Leaman, Zhiyong Lu

      Pages 11-31

   3. Mapping of Biomedical Text to Concepts of Lexicons, Terminologies, and Ontologies

      • Michael Bada

      Pages 33-45

   4. Text Mining for Drug–Drug Interaction

      • Heng-Yi Wu, Chien-Wei Chiang, Lang Li

      Pages 47-75

   5. Biological Information Extraction and Co-occurrence Analysis

      • Georgios A. Pavlopoulos, Vasilis J. Promponas, Christos A. Ouzounis, Ioannis Iliopoulos

      Pages 77-92

4. Seeking New Biology by Unlocking “Hidden” Information

   1. Front Matter

      Pages 93-93

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   2. Roles for Text Mining in Protein Function Prediction

      • Karin M. Verspoor

      Pages 95-108

   3. Functional Molecular Units for Guiding Biomarker Panel Design

      • Andreas Heinzel, Irmgard Mühlberger, Raul Fechete, Bernd Mayer, Paul Perco

      Pages 109-133

   4. Mining Biological Networks from Full-Text Articles

      • Jan Czarnecki, Adrian J. Shepherd

      Pages 135-145

   5. Scientific Collaboration Networks Using Biomedical Text

      • Siddhartha R. Jonnalagadda, Philip S. Topham, Edward J. Silverman, Ryan G. Peeler

      Pages 147-157

   6. Predicting Future Discoveries from Current Scientific Literature

      • Ingrid Petrič, Bojan Cestnik

      Pages 159-168

5. From Electronic Biology to Drug Discovery and Development

   1. Front Matter

      Pages 169-169

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   2. Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery

      • Deepak K. Rajpal, Xiaoyan A. Qu, Johannes M. Freudenberg, Vinod D. Kumar

      Pages 171-206

   3. Integrative Literature and Data Mining to Rank Disease Candidate Genes

      • Chao Wu, Cheng Zhu, Anil G. Jegga

      Pages 207-226

   4. Role of Text Mining in Early Identification of Potential Drug Safety Issues

      • Mei Liu, Yong Hu, Buzhou Tang

      Pages 227-251

   5. Systematic Drug Repurposing Through Text Mining

      • Luis B. Tari, Jagruti H. Patel

      Pages 253-267

   6. Mining the Electronic Health Record for Disease Knowledge

      • Elizabeth S. Chen, Indra Neil Sarkar

      Pages 269-286

6. Back Matter

   Pages 287-288

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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.

• biomedical literature
• domain-specific mining methods
• domains
• drug discovery
• genomics
• information retrieval
• integrated text-mining approaches
• retrieval methods
• systems biology

• GlaxoSmithKline, King of Prussia, USA

  Vinod D. Kumar

• GlaxoSmithKline, Hitchin, United Kingdom

  Hannah Jane Tipney

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