Machine-Learning based sequence analysis, bioinformatics & nanopore transduction detection

Stephen Winters-Hilt

ISBN 10: 1257645250 / ISBN 13: 9781257645251

Editore: Lulu.Com, 2011

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nach der Bestellung gedruckt Neuware - Printed after ordering - This is intended to be a simple and accessible book on machine learning methods and their application in computational genomics and nanopore transduction detection. This book has arisen from eight years of teaching one-semester courses on various machine-learning, cheminformatics, and bioinformatics topics. The book begins with a description of ad hoc signal acquisition methods and how to orient on signal processing problems with the standard tools from information theory and signal analysis. A general stochastic sequential analysis (SSA) signal processing architecture is then described that implements Hidden Markov Model (HMM) methods. Methods are then shown for classification and clustering using generalized Support Vector Machines, for use with the SSA Protocol, or independent of that approach. Optimization metaheuristics are used for tuning over algorithmic parameters throughout. Hardware implementations and short code examples of the various methods are also described.

Codice articolo 9781257645251

Dati bibliografici

• Titolo: Machine-Learning based sequence analysis, bioinformatics & nanopore transduction detection
• Editore: Lulu.Com
• Data di pubblicazione: 2011
• Lingua: Inglese
• ISBN 10: 1257645250
• ISBN 13: 9781257645251
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 235 L x 157 A x 28 P (millimetri) 235 millimetri di larghezza per 157 millimetri di altezza per 28 millimetri di profondità
• Peso: 776 grammi

Descrizione articolo

Riassunto

This is intended to be a simple and accessible book on machine learning methods and their application in computational genomics and nanopore transduction detection. This book has arisen from eight years of teaching one-semester courses on various machine-learning, cheminformatics, and bioinformatics topics. The book begins with a description of ad hoc signal acquisition methods and how to orient on signal processing problems with the standard tools from information theory and signal analysis. A general stochastic sequential analysis (SSA) signal processing architecture is then described that implements Hidden Markov Model (HMM) methods. Methods are then shown for classification and clustering using generalized Support Vector Machines, for use with the SSA Protocol, or independent of that approach. Optimization metaheuristics are used for tuning over algorithmic parameters throughout. Hardware implementations and short code examples of the various methods are also described.

Product Description

Book by WintersHilt Stephen