Biomedical Literature Mining

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.

1.      Introduction to Biomedical Literature Text mining: Context and Objectives

Jeffrey D. Saffer and Vicki L. Burnett

 

Part I: Principles of Text mining: Getting Started

 

2.      Accessing Biomedical Literature in the Current Information Landscape

Ritu Khare, Robert Leaman and  Zhiyong Lu

 

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

Mike Bada

 

4.      Drug Interaction Text Mining

Hengyi Wu, ChienWei Chiang, and Lang Li

 

5.      Biological Information Extraction and Co-occurence Analysis: State of the Art and Perspectives 

Georgios Pavlopoulos, Vasilis Promponas, Christos Ouzounis and Ioannis Iliopoulos

 Part II: Seeking new Biology by Unlocking “Hidden” Information

 

6.      Roles of Text Mining in Protein Function Prediction

Karin Verspoor

 

7.      Functional Molecular Units for Guiding Biomarker Panel Design

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

 

8.      Mining Biological Networks from Full-text Articles

Jan Czarnecki  and Adrian J Shepherd

 

9.      Scientific Collaboration Networks using Biomedical Text

Siddhartha Jonnalagadda, Philip Topham, Ryan Peeler, and Edward Silverman

 

10.   Predicting Future Discoveries from Current Scientific Literature

Ingrid Petric, Tanja Urbancic, and Bojan Cestnik

 

 

Part III: From Electronic Biology to Drug Discovery and Development

 

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

Deepak K. Rajpal, Xiaoyan A. Qu, Johannes Freudenberg, and Vinod Kumar

 

12.  Integrating Literature and Data Mining to Rank Disease Candidate Genes

Chao Wu, Cheng Zhu,  and Anil G Jegga

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

Mei Liu, Yong Hu, and Buzhou Tang

 

14.  Systematic Drug Repositioning using Text Mining

Luis Tari and Jagruti Patel

 

15.  Mining the Electronic Health Record for Disease-Specific Knowledge

Elizabeth S. Chen and Indra Neil Sarkar