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Probabilistic Methods For Bioinformatics

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Probabilistic Methods for Bioinformatics

Probabilistic Methods for Bioinformatics Book
Author : Richard E. Neapolitan
Publisher : Morgan Kaufmann
Release : 2009-06-12
ISBN : 9780080919362
Language : En, Es, Fr & De

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Book Description :

The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics. Shares insights about when and why probabilistic methods can and cannot be used effectively; Complete review of Bayesian networks and probabilistic methods with a practical approach.

Probabilistic Methods for Bionformatics

Probabilistic Methods for Bionformatics Book
Author : Richard E. Neapolitan
Publisher : Unknown
Release : 2009
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Probabilistic Methods for Bionformatics book written by Richard E. Neapolitan, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Probabilistic Modeling in Bioinformatics and Medical Informatics

Probabilistic Modeling in Bioinformatics and Medical Informatics Book
Author : Dirk Husmeier,Richard Dybowski,Stephen Roberts
Publisher : Springer Science & Business Media
Release : 2006-03-30
ISBN : 1846281199
Language : En, Es, Fr & De

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Book Description :

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Statistical Methods in Bioinformatics

Statistical Methods in Bioinformatics Book
Author : Warren J. Ewens,Gregory R. Grant
Publisher : Springer Science & Business Media
Release : 2013-03-09
ISBN : 1475732473
Language : En, Es, Fr & De

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Book Description :

There was a real need for a book that introduces statistics and probability as they apply to bioinformatics. This book presents an accessible introduction to elementary probability and statistics and describes the main statistical applications in the field.

Contemporary Artificial Intelligence

Contemporary Artificial Intelligence Book
Author : Richard E. Neapolitan
Publisher : CRC Press
Release : 2012-08-23
ISBN : 1466559403
Language : En, Es, Fr & De

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Book Description :

The notion of artificial intelligence (AI) often sparks thoughts of characters from science fiction, such as the Terminator and HAL 9000. While these two artificial entities do not exist, the algorithms of AI have been able to address many real issues, from performing medical diagnoses to navigating difficult terrain to monitoring possible failures of spacecrafts. Exploring these algorithms and applications, Contemporary Artificial Intelligence presents strong AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more. One of the first AI texts accessible to students, the book focuses on the most useful problem-solving strategies that have emerged from AI. In a student-friendly way, the authors cover logic-based methods; probability-based methods; emergent intelligence, including evolutionary computation and swarm intelligence; data-derived logical and probabilistic learning models; and natural language understanding. Through reading this book, students discover the importance of AI techniques in computer science.

Bayesian Methods in Structural Bioinformatics

Bayesian Methods in Structural Bioinformatics Book
Author : Thomas Hamelryck,Kanti Mardia,Jesper Ferkinghoff-Borg
Publisher : Springer
Release : 2012-03-23
ISBN : 3642272258
Language : En, Es, Fr & De

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Book Description :

This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.

Machine Learning in Bioinformatics

Machine Learning in Bioinformatics Book
Author : Yanqing Zhang,Jagath C. Rajapakse
Publisher : John Wiley & Sons
Release : 2009-02-23
ISBN : 9780470397411
Language : En, Es, Fr & De

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Book Description :

An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

Probabilistic Modeling in Bioinformatics and Medical Informatics

Probabilistic Modeling in Bioinformatics and Medical Informatics Book
Author : Richard Dybowski,Dirk Husmeier,Stephen Roberts
Publisher : Unknown
Release : 2005
ISBN : 9786610346653
Language : En, Es, Fr & De

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Book Description :

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Introduction to Mathematical Methods in Bioinformatics

Introduction to Mathematical Methods in Bioinformatics Book
Author : Alexander Isaev
Publisher : Springer
Release : 2006-10-04
ISBN : 3540484264
Language : En, Es, Fr & De

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Book Description :

This book looks at the mathematical foundations of the models currently in use. All existing books on bioinformatics are software-orientated and they concentrate on computer implementations of mathematical models of biology. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.

Statistical Methods in Bioinformatics

Statistical Methods in Bioinformatics Book
Author : W. Warren John Ewens,Gregory Robert Grant
Publisher : Springer Science & Business Media
Release : 2001
ISBN : 9780387952291
Language : En, Es, Fr & De

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Book Description :

Probability theory (i): one random variable. Probability theory (ii); many random variables. Statistics (i): an introduction to statistical inference. Stochastic processes (i): poisson processes and markov chains. Stochastic processes (iii): markov chains. Hidden markov models. Computationally intensive methods. Evolutionary models. Phylogenetic tree estimation. Basic notions in biology. C computational aspects of the binominal and generalized geometric distribution functions. D BLAST: sums of normalized scores. References. Author index. Index.

Statistical Methods in Bioinformatics

Statistical Methods in Bioinformatics Book
Author : Warren J. Ewens,Gregory R. Grant
Publisher : Unknown
Release : 2014-01-15
ISBN : 9781475732481
Language : En, Es, Fr & De

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Book Description :

Download Statistical Methods in Bioinformatics book written by Warren J. Ewens,Gregory R. Grant, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Data Analysis and Classification for Bioinformatics

Data Analysis and Classification for Bioinformatics Book
Author : Arun Jagota
Publisher : Bioinformatics by the Bay
Release : 2000
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

With the explosion of sequence data in public and private databases and the coming explosion of gene expression data in a similar vein, it is becoming increasingly important to understand how to apply well-established data analysis and data classification methods that have been developed in other fields to this field---to try to make sense of the data, to glean biological insights from it, to categorize the data, and to put all of these to good use in industrial applications. This book introduces the main methods of data analysis and of data classification--as applied to sequence and gene expression analysis--to the biologist and to the computer scientist in this field. It contains material that is presently being taught by the author in the course Data Analysis, Modeling, and Visualization for Bioinformatics at the University of California, Santa Cruz Extension to workers in the biotechnology industry in Silicon Valley.

Applications of Machine Learning Techniques to Bioinformatics

Applications of Machine Learning Techniques to Bioinformatics Book
Author : Haifeng Li
Publisher : VDM Publishing
Release : 2008
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Applications of Machine Learning Techniques to Bioinformatics book written by Haifeng Li, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Bioinformatics

Bioinformatics Book
Author : David W. Mount
Publisher : CSHL Press
Release : 2004
ISBN : 9780879697129
Language : En, Es, Fr & De

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Book Description :

As more species' genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories.

Artificial Intelligence and Heuristic Methods in Bioinformatics

Artificial Intelligence and Heuristic Methods in Bioinformatics Book
Author : Paolo Frasconi,Ron Shamir
Publisher : Unknown
Release : 2003
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

The 14 papers consider how various methods in artificial intelligence are applied to problems in bioinformatics. Among the topics are statistical learning and kernel methods in bioinformatics, new machine learning methods for predicting protein topologies, multiple sequence alignments information in structure and function prediction, pattern discovery and the algorithms of surprise, the computational identification of regulatory sites in DNA sequences, computer system gene discovery for promoter structure analysis, and data acquisition and analysis in near-genome-wide expressions screening of tumor suppressor pathways using model cell lines with inducible transcription factors. There is no subject index. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).

Probabilistic Graphical Models for Genetics Genomics and Postgenomics

Probabilistic Graphical Models for Genetics  Genomics and Postgenomics Book
Author : Christine Sinoquet
Publisher : Oxford University Press, USA
Release : 2014
ISBN : 0198709021
Language : En, Es, Fr & De

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Book Description :

At the crossroads between statistics and machine learning, probabilistic graphical models provide a powerful formal framework to model complex data. For instance, Bayesian networks and Markov random fields are two of the most popular probabilistic graphical models. With the rapid advance of high-throughput technologies and their ever decreasing costs, a fast-growing volume of biological data of various types - the so-called ''omics'' - is in need of accurate andefficient methods for modeling, prior to further downstream analysis. As probabilistic graphical models are able to deal with high-dimensional data, it is foreseeable that such models will have aprominent role to play in advances in genome-wide data analyses. Currently, few people are specialists in the design of cutting-edge methods using probabilistic graphical models for genetics, genomics and postgenomics. This seriously hinders the diffusion of such methods. The prime aim of the book is therefore to bring the concepts underlying these advanced models within reach of scientists who are not specialists of these models, but with no concession on theinformativeness of the book. The target readers include researchers and engineers who have to design novel methods for postgenomics data analysis, as well as graduate students starting a Masters or a PhD. Inaddition to an introductory chapter on probabilistic graphical models, a thorough review chapter focusing on selected domains in genetics and fourteen chapters illustrate the design of such advanced approaches in various domains: gene network inference, inference of causal phenotype networks, association genetics, epigenetics, detection of copy number variations, and prediction of outcomes from high-dimensional genomic data. Notably, most examples also illustrate that probabilistic graphicalmodels are well suited for integrative biology and systems biology, hot topics guaranteed to be of lasting interest.

Computational Systems Bioinformatics

Computational Systems Bioinformatics Book
Author : Xiaobo Zhou,Stephen T. C. Wong
Publisher : World Scientific
Release : 2008
ISBN : 9812707042
Language : En, Es, Fr & De

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Book Description :

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.

The British National Bibliography

The British National Bibliography Book
Author : Arthur James Wells
Publisher : Unknown
Release : 2009
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download The British National Bibliography book written by Arthur James Wells, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.