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Probabilistic Methods for Bioinformatics

Probabilistic Methods for Bioinformatics
  • Author : Richard E. Neapolitan
  • Publsiher : Morgan Kaufmann
  • Release : 12 June 2009
  • ISBN : 9780080919362
  • Pages : 424 pages
  • Rating : 1/5 from 1 ratings
GET THIS BOOKProbabilistic Methods for Bioinformatics

Summary:
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 Bioinformatics

Probabilistic Methods for Bioinformatics
  • Author : Richard E. Neapolitan
  • Publisher : Morgan Kaufmann
  • Release : 12 June 2009
GET THIS BOOKProbabilistic Methods for Bioinformatics

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

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Foundations of Algorithms

Foundations of Algorithms
  • Author : Professor Emeritus Rutgers University School of Health Related Professions Craig L Scanlan,Richard Neapolitan,Albert J Heuer,Kumarss Naimipour
  • Publisher : Jones & Bartlett Publishers
  • Release : 31 March 2014
GET THIS BOOKFoundations of Algorithms

Foundations of Algorithms, Fifth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. Ideal for any computer science students with a background in college algebra and discrete structures, the text presents mathematical concepts using standard English and simple notation to maximize accessibility and user-friendliness. Concrete examples, appendices reviewing essential mathematical concepts, and a student-focused approach reinforce theoretical explanations and promote learning and retention. C++ and Java pseudocode help students better understand complex algorithms. A

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Computational Intelligence Methods for Bioinformatics and Biostatistics

Computational Intelligence Methods for Bioinformatics and Biostatistics
  • Author : Enrico Formenti,Roberto Tagliaferri,Ernst Wit
  • Publisher : Springer
  • Release : 15 July 2014
GET THIS BOOKComputational Intelligence Methods for Bioinformatics and Biostatistics

This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2013, held in Nice, France in June 2013. The 19 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on bioinformatics, biostatistics, knowledge based medicine, and data integration and analysis in omic-science.

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Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics
  • Author : Min Li,Jianxin Wang,Yi Pan
  • Publisher : John Wiley & Sons
  • Release : 07 October 2013
GET THIS BOOKAlgorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and

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Artificial Intelligence

Artificial Intelligence
  • Author : Richard E. Neapolitan,Xia Jiang
  • Publisher : CRC Press
  • Release : 12 March 2018
GET THIS BOOKArtificial Intelligence

The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section

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Probabilistic Methods for Financial and Marketing Informatics

Probabilistic Methods for Financial and Marketing Informatics
  • Author : Richard E. Neapolitan,Xia Jiang
  • Publisher : Elsevier
  • Release : 26 July 2010
GET THIS BOOKProbabilistic Methods for Financial and Marketing Informatics

Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems. The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic

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Contemporary Artificial Intelligence

Contemporary Artificial Intelligence
  • Author : Richard E. Neapolitan
  • Publisher : CRC Press
  • Release : 25 August 2012
GET THIS BOOKContemporary Artificial Intelligence

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

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Advances in Biotechnology Research and Application: 2012 Edition

Advances in Biotechnology Research and Application: 2012 Edition
  • Author : Anonim
  • Publisher : ScholarlyEditions
  • Release : 26 December 2012
GET THIS BOOKAdvances in Biotechnology Research and Application: 2012 Edition

Advances in Biotechnology Research and Application / 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biotechnology. The editors have built Advances in Biotechnology Research and Application / 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biotechnology in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Biotechnology Research and Application / 2012 Edition has been produced

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Safety and Reliability. Theory and Applications

Safety and Reliability. Theory and Applications
  • Author : Marko Cepin,Radim Bris
  • Publisher : CRC Press
  • Release : 14 June 2017
GET THIS BOOKSafety and Reliability. Theory and Applications

Safety and Reliability – Theory and Applications contains the contributions presented at the 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017). The book covers a wide range of topics, including: • Accident and Incident modelling • Economic Analysis in Risk Management • Foundational Issues in Risk Assessment and Management • Human Factors and Human Reliability • Maintenance Modeling and Applications • Mathematical Methods in Reliability and Safety • Prognostics and System Health Management • Resilience Engineering • Risk Assessment • Risk Management • Simulation for Safety and Reliability Analysis •

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Foundations of Algorithms

Foundations of Algorithms
  • Author : Richard Neapolitan
  • Publisher : Jones & Bartlett Learning
  • Release : 31 March 2014
GET THIS BOOKFoundations of Algorithms

Foundations of Algorithms, Fifth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. Ideal for any computer science students with a background in college algebra and discrete structures, the text presents mathematical concepts using standard English and simple notation to maximize accessibility and user-friendliness. Concrete examples, appendices reviewing essential mathematical concepts, and a student-focused approach reinforce theoretical explanations and promote learning and retention. C++ and Java pseudocode help students better understand complex algorithms. A

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty

Symbolic and Quantitative Approaches to Reasoning with Uncertainty
  • Author : Weiru Liu
  • Publisher : Springer
  • Release : 25 June 2011
GET THIS BOOKSymbolic and Quantitative Approaches to Reasoning with Uncertainty

This book constitutes the refereed proceedings of the 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2011, held in Belfast, UK, in June/July 2011. The 60 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on argumentation; Bayesian networks and causal networks; belief functions; belief revision and inconsistency handling; classification and clustering; default reasoning and logics for reasoning under uncertainty; foundations of reasoning and

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Lectures on Inductive Logic

Lectures on Inductive Logic
  • Author : Jon Williamson,Professor of Reasoning Inference and Scientific Method Jon Williamson
  • Publisher : Oxford University Press
  • Release : 26 January 2017
GET THIS BOOKLectures on Inductive Logic

Logic is a field studied mainly by researchers and students of philosophy, mathematics and computing. Inductive logic seeks to determine the extent to which the premisses of an argument entail its conclusion, aiming to provide a theory of how one should reason in the face of uncertainty. It has applications to decision making and artificial intelligence, as well as how scientists should reason when not in possession of the full facts. In this book, Jon Williamson embarks on a quest

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