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Statistical Bioinformatics with R

Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications.

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Basics of Bioinformatics

in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics;

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Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;

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Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;

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Statistical Modelling in Biostatistics and Bioinformatics

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The;

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Statistical Modelling in Biostatistics and Bioinformatics

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The;

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Statistical Modelling and Machine Learning Principles for Bioinformatics Techniq

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting t;...

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BIOS Instant Notes in Bioinformatics

into three parts: the first being an introduction to bioinformatics in biology; the second covering the physical, mathematical, statistical and;

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Computational Intelligence Techniques for Comparative Genomics

statistical analysis approach to effectively study the disorders and possible causes along with medical applications.;

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Statistical Bioinformatics

data sets in biology. Chaptersbegin with a description of a statistical concept and a currentexample from biomedical research, followed by more;

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Knowledge Based Bioinformatics

to genomic and proteomic research. This book discussesknowledge-based and statistical approaches, along with applicationsin bioinformatics;

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Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology

Gene-environment (G x E) interaction analysis is a statistical method for clarifying G x E interactions applicable to a phenotype or a;

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Fundamentals of Bioinformatics

Bioinformatics is an upcoming discipline of Life Sciences. It is an integration of computer science, and mathematical and statistical;

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Bioinformatics Research and Applications

; phylogenetics; sequence analysis; and statistical methods.;

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Problem Solving Handbook in Computational Biology and Bioinformatics

Bioinformatics is growing by leaps and bounds; theories/algorithmsstatistical techniques are constantly evolving. Nevertheless, a core;

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Bioinformatics

This title includes a number of Open Access chapters. The book introduces bioinformatic and statistical methodology and shows;

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New Developments In Biostatistics And Bioinformatics

, statistical methods for epidemiology, and bioinformatics.;

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Bioinformatics

This title includes a number of Open Access chapters. The book introduces bioinformatic and statistical methodology and shows approaches;

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The Problem Solving Handbook for Computational Biology and Bioinformatics

Bioinformatics is growing by leaps and bounds; theories/algorithmsstatistical techniques are constantly evolving. Nevertheless, a core;

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Bioinformatics and Computational Biology

, sequence alignment, molecular evolution, next-generation sequencing, systems biology, and statistical computing using R. The book also presents a;

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Introduction to Bioinformatics

can help solve biological problems. Requiring only a limited mathematical and statistical background, the book shows how to efficiently apply;

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Introduction to Bioinformatics

can help solve biological problems. Requiring only a limited mathematical and statistical background, the book shows how to efficiently apply;

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Next Generation Microarray Bioinformatics

current computational and statistical methods to analyze and interpreting both microarray and NGS data. These methods and techniques include;

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Structural Bioinformatics Handbook

structures. The chapters included herein discuss concepts of genome research and gene networks, stimulating biological networks, statistical and;

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Bioinformatics and Molecular Evolution

, biological databases, pattern recognition, and applications to genomics, microarrays, and proteomics emphasizes the theoretical and statistical;

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Statistical Paradigms

This volume consists of a collection of research articles on classical and emerging Statistical Paradigms parametric, non-parametric and;

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Bioinformatics with Python Cookbook - Second Edition: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge rese

, metagenomics, automating analysis, population genetics, and more Explore various statistical and machine learning techniques for bioinformatics data;

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