Springer Optimization and Its Applications

By: Panos M. Pardalos (Editor), Vladimir L. Boginski (Editor), Alkis Vazacopoulos (Editor)

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Hardcover | 15 March 2007

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600 Pages

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23.5 x 15.88 x 3.81

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This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.

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"This book is an in-depth look at 'the development of appropriate methods for extracting useful information' from data in biomedicine. ... is aimed at scientists and practitioners in the fields of biomedicine, engineering, mathematics, and computer science as well as graduate students and is appropriate for a variety of readers. ... A well compiled volume on the application of data mining to biomedicine, this book will be a welcome addition to the literature." (Nicole Mitchell, Doody's Review Service, August, 2008)

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Published: 19th November 2010

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Preface	p. ix
List of Contributors	p. xi
Recent Methodological Developments for Data Mining Problems in Biomedicine
Pattern-Based Discriminants in the Logical Analysis of Data	p. 3
Exploring Microarray Data with Correspondence Analysis	p. 25
An Ensemble Method of Discovering Sample Classes Using Gene Expression Profiling	p. 39
CpG Island Identification with Higher Order and Variable Order Markov Models	p. 47
Data Mining Algorithms for Virtual Screening of Bioactive Compounds	p. 59
Sparse Component Analysis: a New Tool for Data Mining	p. 91
Data Mining Via Entropy and Graph Clustering	p. 117
Molecular Biology and Pooling Design	p. 133
An Optimization Approach to Identify the Relationship between Features and Output of a Multi-label Classifier	p. 141
Classifying Noisy and Incomplete Medical Data by a Differential Latent Semantic Indexing Approach	p. 169
Ontology Search and Text Mining of MEDLINE Database	p. 177
Data Mining Techniques in Disease Diagnosis
Logical Analysis of Computed Tomography Data to Differentiate Entities of Idiopathic Interstitial Pneumonias	p. 193
Diagnosis of Alport Syndrome by Pattern Recognition Techniques	p. 209
Clinical Analysis of the Diagnostic Classification of Geriatric Disorders	p. 231
Data Mining Studies in Genomics and Proteomics
A Hybrid Knowledge Based-Clustering Multi-Class SVM Approach for Genes Expression Analysis	p. 261
Mathematical Programming Formulations for Problems in Genomics and Proteomics	p. 275
Inferring the Origin of the Genetic Code	p. 291
Deciphering the Structures of Genomic DNA Sequences Using Recurrence Time Statistics	p. 321
Clustering Proteomics Data Using Bayesian Principal Component Analysis	p. 339
Bioinformatics for Traumatic Brain Injury: Proteomic Data Mining	p. 363
Characterization and Prediction of Protein Structure
Computational Methods for Protein Fold Prediction: an Ab-initio Topological Approach	p. 391
A Topological Characterization of Protein Structure	p. 431
Applications of Data Mining Techniques to Brain Dynamics Studies
Data Mining in EEG: Application to Epileptic Brain Disorders	p. 459
Information Flow in Coupled Nonlinear Systems: Application to the Epileptic Human Brain	p. 483
Reconstruction of Epileptic Brain Dynamics Using Data Mining Techniques	p. 505
Automated Seizure Prediction Algorithm and its Statistical Assessment: A Report from Ten Patients	p. 517
Seizure Predictability in an Experimental Model of Epilepsy	p. 535
Network-Based Techniques in EEG Data Analysis and Epileptic Brain Modeling	p. 559
Index	p. 575
Table of Contents provided by Publisher. All Rights Reserved.

Springer Optimization and Its Applications

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