Biological data mining / edited by Jake Y. Chen, Stefano Lonardi.

Format:

Book

Contributor:

Chen, Jake.

Lonardi, Stefano

Clarence J. Marshall Memorial Library Fund.

Series:

Chapman & Hall/CRC data mining and knowledge discovery series

Language:

English

Subjects (All):

Bioinformatics.

Data mining.

Computational biology.

Physical Description:

xx, 713 pages : illustrations ; 25 cm.

Place of Publication:

Boca Raton, FL : Chapman & Hall/CRC, [2010]

Summary:

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting 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 challenge 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.

Features

Provides comprehensive coverage of biological sequences, structures, Omics, ontology, literature mining, and biomedical applications

Integrates biological concepts with computational data mining techniques

Includes case studies of biological applications

Presents both basic concepts and advanced techniques

Incorporates contributions from a team of experts who are active in biological data mining research

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.

Contents:

Part I Sequence, Structure, and Function 1

1 Consensus Structure Prediction for RNA Alignments / Junilda Spirollari, Jason T. L. Wang 3

2 Invariant Geometric Properties of Secondary Structure Elements in Proteins / Matteo Comin, Concettina Guerra, Giuseppe Zanotti 27

3 Discovering 3D Motifs in RNA / Alberto Apostolico, Giovanni Ciriello, Concettina Guerra, Christine E. Heitsch 49

4 Protein Structure Classification Using Machine Learning Methods / Yazhene Krishnaraj, Chandan Reddy 69

5 Protein Surface Representation and Comparison: New Approaches in Structural Proteomics / Lee Sael, Daisuke Kihara 89

6 Advanced Graph Mining Methods for Protein Analysis / Yi-Ping Phoebe Chen, Jia Rong, Gang Li 111

7 Predicting Local Structure and Function of Proteins / Huzefa Rangwala, George Karypis 137

Part II Genomics, Transcriptomics, and Proteomics 161

8 Computational Approaches for Genome Assembly Validation / Jeong-Hyeon Choi, Haixu Tang, Sun Kim, Mihai Pop 163

9 Mining Patterns of Epistasis in Human Genetics / Jason H. Moore 187

10 Discovery of Regulatory Mechanisms from Gene Expression Variation by eQTL Analysis / Yang Huang, Jie Zheng, Teresa M. Przytycka 205

11 Statistical Approaches to Gene Expression Microarray Data Preprocessing / Megan Kong, Elizabeth McClellan, Richard H. Scheuermann, Monnie McGee 229

12 Application of Feature Selection and Classification to Computational Molecular Biology / Paola Bertolazzi, Giovanni Felici, Giuseppe Lancia 257

13 Statistical Indices for Computational and Data Driven Class Discovery in Microarray Data / Raffaele Giancarlo, Davide Scaturro, Filippo Utro 295

14 Computational Approaches to Peptide Retention Time Prediction for Proteomics / Xiang Zhang, Cheolhwan Oh, Catherine P. Riley, Hyeyoung Cho, Charles Buck 337

Part III Functional and Molecular Interaction Networks 351

15 Inferring Protein Functional Linkage Based on Sequence Information and Beyond / Li Liao 353

16 Computational Methods for Unraveling Transcriptional Regulatory Networks in Prokaryotes / Dongsheng Che, Guojun Li 377

17 Computational Methods for Analyzing and Modeling Biological Networks / Natasa Przulj, Tijana Milenkovic 397

18 Statistical Analysis of Biomolecular Networks / Jing-Dong J. Han, Chris J. Needham 429

Part IV Literature, Ontology, and Knowledge Integration 447

19 Beyond Information Retrieval: Literature Mining for Biomedical Knowledge Discovery / Javed Mostafa, Kazuhiro Seki, Weimao Ke 449

20 Mining Biological Interactions from Biomedical Texts for Efficient Query Answering / Muhammad Abulaish, Lipika Dey, Jahiruddin 485

21 Ontology-Based Knowledge Representation of Experiment Metadata in Biological Data Mining / Richard H. Scheuermann, Megan Kong, Carl Dahlke, Jennifer Cai, Jamie Lee, Yu Qian, Burke Squires, Patrick Dunn, Jeff Wiser, Herb Hagler, Barry Smith, David Karp 529

22 Redescription Mining and Applications in Bioinformatics / Naren Ramakrishnan, Mohammed J. Zaki 561

Part V Genome Medicine Applications 587

23 Data Mining Tools and Techniques for Identification of Biomarkers for Cancer / Mick Correll, Simon Beaulah, Robin Munro, Jonathan Sheldon, Yike Guo, Hai Hu 589

24 Cancer Biomarker Prioritization: Assessing the in vivo Impact of in vitro Models by in silico Mining of Microarray Database, Literature, and Gene Annotation / Chia-Ju Lee, Zan Huang, Hongmei Jiang, John Crispino, Simon Lin 615

25 Biomarker Discovery by Mining Glycomic and Lipidomic Data / Haixu Tang, Mehmet Dalkilic, Yehia Mechref 627

26 Data Mining Chemical Structures and Biological Data / Glenn J. Myatt, Paul E. Blower 649.

Notes:

Includes bibliographical references and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Clarence J. Marshall Memorial Library Fund.

ISBN:

9781420086843

1420086847

OCLC:

226357310