Kernel Methods In Computational Biology
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Kernel Methods In Computational Biology
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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2004
Kernel Methods In Computational Biology written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
A detailed overview of current research in kernel methods and their application to computational biology.
Kernel Methods In Bioengineering Signal And Image Processing
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Author : Gustavo Camps-Valls
language : en
Publisher: IGI Global
Release Date : 2007-01-01
Kernel Methods In Bioengineering Signal And Image Processing written by Gustavo Camps-Valls and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-01 with Technology & Engineering categories.
"This book presents an extensive introduction to the field of kernel methods and real world applications. The book is organized in four parts: the first is an introductory chapter providing a framework of kernel methods; the others address Bioegineering, Signal Processing and Communications and Image Processing"--Provided by publisher.
Handbook Of Statistical Bioinformatics
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Author : Henry Horng Lu
language : en
Publisher:
Release Date : 2011-05-19
Handbook Of Statistical Bioinformatics written by Henry Horng Lu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-19 with categories.
Learning With Kernels
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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2002
Learning With Kernels written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
A comprehensive introduction to Support Vector Machines and related kernel methods.
Kernel Methods In Chemo And Bioinformatics
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Author : Holger Fröhlich
language : en
Publisher: Logos Verlag Berlin
Release Date : 2006
Kernel Methods In Chemo And Bioinformatics written by Holger Fröhlich and has been published by Logos Verlag Berlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Bioinformatics categories.
This thesis is devoted to the finding of possible solutions for some machine learning related problems in modern chemo- and bioinformatics by means of so-called kernel methods. They are a special family of learning algorithms that have attracted a growing interest during the last years due to their good theoretical foundation and many successful practical applications in various disciplines. At the core of all kernel methods is the usage of a kernel function, which can be thought of as a special similarity measure between arbitrary objects. At the beginning of this thesis fundamentals and principles of kernel machines are reviewed. Afterwards a novel algorithm for model selection for Support Vector Machines (SVMs) in classification and regression is proposed, which is based on ideas from global optimization theory. It does not make any assumptions about special properties of the kernel function, like differentiability, and is highly efficient. Experimental comparisons to existing algorithms yield good results. After this we turn our point of interest to applications of kernel methods in chemo- and bioinformatics: For the ADME in silico prediction problem in modern drug discovery descriptor and graph-based representations of molecules are investigated. A descriptor selection algorithm is proposed, which can improve the statistical stability of an existing method. Furthermore, a novel class of specialized kernel functions is introduced that allows the comparison of a pair of molecules on a graph-based level. Various combinations of graph and descriptor-based representations are investigated, which on one hand allow the incorporation of expert domain knowledge and on the other hand the integration of different notions of molecular similarity in one SVM model. Furthermore, a reduced graph representation for molecular structures is proposed, in which certain structural elements are condensed in one node of the graph. Our experiments indicate that with our method improvements of the prediction performance compared to state-of-the-art modelling approaches can be achieved. At the same time our method is computationally rather cheap, unified and highly flexible. Another question, that is examined in the content of this thesis, is, which features of the membrane potentiel (MP) determine the generation of action potentials (APs) in cortical neurons in vivo. SVMs are trained to predict the occurrence of an AP before its onset based on several extracted features of the MP. A specialized feature selection algorithm is then used to select the most important features simultaneously in several in vivo recordings. In conclusion we find that the occurrence of an AP not only depends on the value of the MP shortly before AP onset, but also on the MP rate of change, the increase of the membrane potential several ms before AP onset, and the long range mean MP. Our findings systematically extend investigations by other researchers and are partially also confirmed by their results. As a last application of kernel methods in this thesis, we deal with the problem of clustering genes with regard to their function based on their Gene Ontology (GO) annotation. For this purpose specialized kernel functions are developed, which measure the similarity between gene products with respect to the structure of the GO graph. Using several clustering algorithms, like kernel k-means, spectral clustering and average linkage, we can detect meaningful clusters with our method. Applications to other ontologies or taxonomies in principle are possible.
Methods In Computational Biology
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Author : Ross Carlson
language : en
Publisher: MDPI
Release Date : 2019-07-03
Methods In Computational Biology written by Ross Carlson and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-03 with Science categories.
Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections: • Reviews of Computational Methods • Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels • The Interface of Biotic and Abiotic Processes • Processing of Large Data Sets for Enhanced Analysis • Parameter Optimization and Measurement
Computational Systems Bioinformatics
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Author : Xiaobo Zhou
language : en
Publisher: World Scientific
Release Date : 2008
Computational Systems Bioinformatics written by Xiaobo Zhou and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Science categories.
Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields. This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.
Biomolecular Networks
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Author : Luonan Chen
language : en
Publisher: John Wiley & Sons
Release Date : 2009-06-29
Biomolecular Networks written by Luonan Chen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-29 with Computers categories.
Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.
Learning Theory And Kernel Machines
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Author : Bernhard Scholkopf
language : en
Publisher:
Release Date : 2014-01-15
Learning Theory And Kernel Machines written by Bernhard Scholkopf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Algorithms In Computational Molecular Biology
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Author : Mourad Elloumi
language : en
Publisher: John Wiley & Sons
Release Date : 2011-04-04
Algorithms In Computational Molecular Biology written by Mourad Elloumi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-04 with Science categories.
This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.