Data Mining for Systems Biology

The post-genomic revolution is witnessing the generation of petabytes of data annually, with deep implications ranging across evolutionary theory, developmental biology, agriculture, and disease processes. Data Mining for Systems Biology: Methods and Protocols, surveys and demonstrates the science and technology of converting an unprecedented data deluge to new knowledge and biological insight. The volume is organized around two overlapping themes, network inference and functional inference. 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 protocols, and key tips on troubleshooting and avoiding known pitfalls.

Authoritative and practical, Data Mining for Systems Biology: Methods and Protocols also seeks to aid researchers in the further development of databases, mining and visualization systems that are central to the paradigm altering discoveries being made with increasing frequency.

• Functional Inference
• Network Inference
• genotype
• heterogeneous datasets
• metabolism
• nucleic acids
• phenotype
• post-genomic revolution
• protein-DNA Interactions
• protein-protein interactions
• Systems Biology

• , Institute for Chemical Research, Kyoto University, Kyoto, Japan

  Hiroshi Mamitsuka

• Dept. Biomedical Engineering, Boston University, Boston, USA

  Charles DeLisi

• Inst. Chemical Research, Bioinformatics Center, Kyoto University, Uji, Japan

  Minoru Kanehisa

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