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Biological Data Mining

Biological Data Mining

Interesting Research Book in Biological Data Mining

Author(s) Name:  Jake Y. Chen, Stefano Lonardi

About the Book:

   eflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics.
   The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications.
   This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

Table of Contents

  •   Consensus Structure Prediction for RNA Alignments
      Invariant Geometric Properties of Secondary Structure Elements in Proteins
      Discovering 3D Motifs in RNA
      Protein Structure Classification Using Machine Learning Methods
      Protein Surface Representation and Comparison: New Approaches in Structural Proteomics
      Advanced Graph Mining Methods for Protein Analysis
      Predicting Local Structure and Function of Proteins
  •   Computational Approaches for Genome Assembly Validation
      Mining Patterns of Epistasis in Human Genetics
      Discovery of Regulatory Mechanisms from Gene Expression Variation by eQTL Analysis
      Statistical Approaches to Gene Expression Microarray Data Preprocessing
      Application of Feature Selection and Classification to Computational Molecular Biology
      Statistical Indices for Computational and Data-Driven Class Discovery in Microarray Data
      Computational Approaches to Peptide Retention Time Prediction for Proteomics
  •   Inferring Protein Functional Linkage Based on Sequence Information and Beyond
      Computational Methods for Unraveling Transcriptional Regulatory Networks in Prokaryotes
      Computational Methods for Analyzing and Modeling Biological Networks
  •   Beyond Information Retrieval: Literature Mining for Biomedical Knowledge Discovery
      Mining Biological Interactions from Biomedical Texts for Efficient Query Answering
      Ontology-Based Knowledge Representation of Experiment Metadata in Biological Data Mining
      Redescription Mining and Applications in Bioinformatics
  •   Data Mining Tools and Techniques for Identification of Biomarkers for Cancer
      Cancer Biomarker Prioritization: Assessing the in vivo Impact of in vitro Models by in silico Mining of Microarray Database
      Biomarker Discovery by Mining Glycomic and Lipidomic Data
      Data Mining Chemical Structures and Biological Data

    ISBN:  9781420086843

    Publisher:  Chapman and Hall/CRC

    Year of Publication:  2009

    Book Link:  Home Page Url