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Author	Baldi, Pierre.
Title	Bioinformatics : the machine learning approach / Pierre Baldi, Søren Brunak.
Imprint	Cambridge, Mass. : MIT Press, [2001]
	©2001
Edition	Second edition.

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LOCATION	CALL #	STATUS	MESSAGE
MUSKINGUM STACKS	QH506 .B35 2001	AVAILABLE

Author	Baldi, Pierre.
Series	Adaptive computation and machine learning
	Adaptive computation and machine learning.
Subject	Bioinformatics.
	Molecular biology -- Computer simulation.
	Molecular biology -- Mathematical models.
	Neural networks (Computer science)
	Machine learning.
	Markov processes.
	Computational Biology -- methods.
	Artificial Intelligence.
	Markov Chains.
	Models, Theoretical.
	Neural Networks, Computer.
Alt Name	Brunak, Søren.

Table of Contents
	Series Foreword
	Preface
1	Introduction	1
2	Machine-Learning Foundations: The Probabilistic Framework	47
3	Probabilistic Modeling and Inference: Examples	67
4	Machine Learning Algorithms	81
5	Neural Networks: The Theory	99
6	Neural Networks: Applications	113
7	Hidden Markov Models: The Theory	165
8	Hidden Markov Models: Applications	189
9	Probabilistic Graphical Models in Bioinformatics	225
10	Probabilistic Models of Evolution: Phylogenetic Trees	265
11	Stochastic Grammars and Linguistics	277
12	Microarrays and Gene Expression	299
13	Internet Resources and Public Databases	323
	A: Statistics	347
	B: Information Theory, Entropy, and Relative Entropy	357
	C: Probabilistic Graphical Models	365
D	HMM Technicalities, Scaling, Periodic Architectures, State Functions, and Dirichlet Mixtures	375
E	Gaussian Processes, Kernel Methods, and Support Vector Machines	387
	F: Symbols and Abbreviations	399
	References	409
	Index	447

LOCATION	CALL #	STATUS	MESSAGE
MUSKINGUM STACKS	QH506 .B35 2001	AVAILABLE

Author	Baldi, Pierre.
Series	Adaptive computation and machine learning
	Adaptive computation and machine learning.
Subject	Bioinformatics.
	Molecular biology -- Computer simulation.
	Molecular biology -- Mathematical models.
	Neural networks (Computer science)
	Machine learning.
	Markov processes.
	Computational Biology -- methods.
	Artificial Intelligence.
	Markov Chains.
	Models, Theoretical.
	Neural Networks, Computer.
Alt Name	Brunak, Søren.
Description	xxi, 452 pages : illustrations ; 24 cm.
Edition	Second edition.
Note	"A Bradford book"
Bibliography Note	Includes bibliographical references (p. 409-445).
Contents	Introduction -- Machine-learning foundations : the probabilistic framework -- Probabilistic modeling and inference : examples -- Machine learning algorithms -- Neural networks : the theory -- Neural networks : applications -- Hidden Markov models: the theory -- Hidden Markov models: applications -- Probabilistic graphical models in bioinformatics -- Probabilistic models of evolution : phylogenitc trees -- Stochastic grammars and linguistics -- Microarrays and gene expression -- Internet resources and public databases --
ISBN	026202506X (hc. : alk. paper)
OCLC #	45951728

Table of Contents
	Series Foreword
	Preface
1	Introduction	1
2	Machine-Learning Foundations: The Probabilistic Framework	47
3	Probabilistic Modeling and Inference: Examples	67
4	Machine Learning Algorithms	81
5	Neural Networks: The Theory	99
6	Neural Networks: Applications	113
7	Hidden Markov Models: The Theory	165
8	Hidden Markov Models: Applications	189
9	Probabilistic Graphical Models in Bioinformatics	225
10	Probabilistic Models of Evolution: Phylogenetic Trees	265
11	Stochastic Grammars and Linguistics	277
12	Microarrays and Gene Expression	299
13	Internet Resources and Public Databases	323
	A: Statistics	347
	B: Information Theory, Entropy, and Relative Entropy	357
	C: Probabilistic Graphical Models	365
D	HMM Technicalities, Scaling, Periodic Architectures, State Functions, and Dirichlet Mixtures	375
E	Gaussian Processes, Kernel Methods, and Support Vector Machines	387
	F: Symbols and Abbreviations	399
	References	409
	Index	447

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