Chemoinformatics and advanced machine learning perspectives : complex computational methods and collaborative techniques (eBook, 2011) [WorldCat.org]
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Chemoinformatics and advanced machine learning perspectives : complex computational methods and collaborative techniques
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Chemoinformatics and advanced machine learning perspectives : complex computational methods and collaborative techniques

Author: Huma M Lodhi; Yoshihiro Yamanishi
Publisher: Hershey, PA : Medical Information Science Reference, ©2011.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Lodhi, Huma M.
Chemoinformatics and advanced machine learning perspectives.
Hershey, PA : Medical Information Science Reference, ©2011
(DLC) 2009054321
(OCoLC)468978179
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Huma M Lodhi; Yoshihiro Yamanishi
ISBN: 9781615209125 1615209123
OCLC Number: 688186466
Description: 1 online resource (xvii, 400 pages) : illustrations
Contents: Machine generated contents note: Section 1 Similarity Design in Chemical Space --
ch. 1 Graph Kernels for Chemoinformatics / Koji Tsuda --
ch. 2 Optimal Assignment Kernels for ADME in Silico Prediction / Holger Frohlich --
ch. 3 3D Ligand-Based Virtual Screening with Support Vector Machines / Jean-Philipe Vert --
ch. 4 Simulation Study of the Use of Similarity Fusion for Virtual Screening / Peter Willett --
ch. 5 Structure-Activity Relationships by Autocorrelation Descriptors and Genetic Algorithms / Roberto Todeschini --
Section 2 Graph-Based Approaches in Chemoinformatics --
ch. 6 Graph Mining in Chemoinformatics / Koji Tsuda --
ch. 7 Protein Homology Analysis for Function Prediction with Parallel Sub-Graph Isomorphism / Yang Zhang --
Section 3 Statistical and Bayesian Approaches for Virtual Screenin --
ch. 8 Advanced PLS Techniques in Chemometrics and Their Applications to Molecular Design / Kimito Funatsu --
ch. 9 Nonlinear Partial Least Squares: An Overview / Roman Rosipal --
ch. 10 Virtual Screening Methods Based on Bayesian Statistics / Jurgen Bajorath --
ch. 11 Learning Binding Affinity from Augmented High Throughput Screening Data / Malcolm D. Walkinshaw --
Section 4 Machine Learning Approaches for Drug Discovery, Toxicology, and Biological Systems --
ch. 12 Application of Machine Leaning in Drug Discovery and Development / Shuxing Zhang --
ch. 13 Learning and Prediction of Complex Molecular Structure-Property Relationships: Issues and Strategies for Modeling Intestinal Absorption for Drug Discovery / Rahul Singh --
ch. 14 Learning Methodologies for Detection and Classification of Mutagens / Huma Lodhi --
ch. 15 Brain-like Processing and Classification of Chemical Data: An Approach Inspired by the Sense of Smell / Gisbert Schneider --
Section 5^ Note continued: ch. 16 Prediction of Compound-Protein Interactions with Machine Learning Methods / Hisashi Kashima --
ch. 17 Chemoinformatics on Metabolic Pathways: Attaching Biochemical Information on Putative Enzymatic Reactions / Masaaki Kotera.
Responsibility: Huma Lodhi, Yoshihiro Yamanashi.

Abstract:

Provides an overview of current research in machine learning and applications to chemoinformatics tasks. As a timely compendium of research, this book offers perspectives on key elements that are  Read more...

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