Der Artikel ist weiterhin als ^^OTHERCONDITION^^ verfügbar.
Autor: Pradipta Maji
ISBN-13: 9783319056302
Einband: eBook
Seiten: 304
Sprache: Englisch
eBook Typ: PDF
eBook Format: eBook
Kopierschutz: Adobe DRM [Hard-DRM]
Systemvoraussetzungen
Der Artikel wird am Ende des Bestellprozesses zum Download zur Verfügung gestellt.

Scalable Pattern Recognition Algorithms

Applications in Computational Biology and Bioinformatics
Geben Sie Ihre Bewertung ab!  
Wir verlosen jeden Monat unter allen freigegebenen Rezensionen
3 Gutscheine im Wert von 20 Euro. Teilnahmebedingungen
This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
Introduction to Pattern Recognition and BioinformaticsPart I ClassificationNeural Network Tree for Identification of Splice Junction and Protein Coding Region in DNADesign of String Kernel to Predict Protein Functional Sites Using Kernel-Based ClassifiersPart II Feature SelectionRough Sets for Selection of Molecular Descriptors to Predict Biological Activity of Moleculesf -Information Measures for Selection of Discriminative Genes from Microarray DataIdentification of Disease Genes Using Gene Expression and Protein-Protein Interaction DataRough Sets for Insilico Identification of Differentially Expressed miRNAsPart III ClusteringGrouping Functionally Similar Genes from Microarray Data Using Rough-Fuzzy ClusteringMutual Information Based Supervised Attribute Clustering for Microarray Sample ClassificationPossibilistic Biclustering for Discovering Value-Coherent Overlapping d -BiclustersFuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images
Recent advances in high-throughput technologies have resulted in a deluge of biological information. Yet the storage, analysis, and interpretation of such multifaceted data require effective and efficient computational tools.This unique text/reference addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The book reviews both established and cutting-edge research, following a clear structure reflecting the major phases of a pattern recognition system: classification, feature selection, and clustering. The text provides a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics.Topics and features: reviews the development of scalable pattern recognition algorithms for computational biology and bioinformatics; integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.This important work will be of great use to graduate students and researchers in the fields of computer science, electrical and biomedical engineering. Researchers and practitioners involved in pattern recognition, machine learning, computational biology and bioinformatics, data mining, and soft computing will also find the book invaluable.

Zu diesem Artikel ist noch keine Rezension vorhanden.
Helfen sie anderen Besuchern und verfassen Sie selbst eine Rezension.

 

Rezensionen

Autor: Pradipta Maji
ISBN-13 :: 9783319056302
ISBN: 3319056301
Verlag: Springer International Publishing
Seiten: 304
Sprache: Englisch
Auflage 2014
Sonstiges: Ebook