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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.

Statistical Modelling in Biostatistics and Bioinformatics

Statistical Modelling in Biostatistics and Bioinformatics Book
Author : Gilbert MacKenzie,Defen Peng
Publisher : Springer Science & Business Media
Release : 2014-05-08
ISBN : 3319045792
Language : En, Es, Fr & De

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Book Description :

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and funded by the Science Foundation Ireland under its Mathematics Initiative.

Statistical Bioinformatics with R

Statistical Bioinformatics with R Book
Author : Sunil K. Mathur
Publisher : Academic Press
Release : 2010
ISBN : 9780123751041
Language : En, Es, Fr & De

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Book Description :

Designed for a one or two semester senior undergraduate or graduate bioinformatics course, Statistical Bioinformatics takes a broad view of the subject - not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications. The inclusion of R code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics. Ancillary list: * Online ISM- http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123751041 * Companion Website w/ R code and Ebook- http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123751041 * Powerpoint slides- http://textbooks.elsevier.com/web/Manuals.aspx?isbn=9780123751041 Integrates biological, statistical and computational concepts Inclusion of R & SAS code Provides coverage of complex statistical methods in context with applications in bioinformatics Exercises and examples aid teaching and learning presented at the right level Bayesian methods and the modern multiple testing principles in one convenient book

Applied Computational Biology and Statistics in Biotechnology and Bioinformatics

Applied Computational Biology and Statistics in Biotechnology and Bioinformatics Book
Author : Ajit Kumar Roy
Publisher : New India Publishing
Release : 2012-01-15
ISBN : 9789380235929
Language : En, Es, Fr & De

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Book Description :

The book entitled "Applied Computational Biology and Statistics in Biotechnology and Bioinformatics" is aimed to cater to the growing demand of academia, researchers and commercial ventures. Altogether there are forty four chapters divided into the following broad sections like 1. Bioinformatics, Genomics and Proteomics, 2. Phylogeny 3. Drug Design and Epigenomics 4. Advanced Computational Tools and Techniques 5. Statistical methods for computational biology, data mining and visualization 6. Socio Economics and Ethics. This book presents the foundations of key problems in computational molecular biology and bioinformatics. It contains basic molecular biology concepts, tools, techniques and ways to measure sequence similarity, presents simple applications of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of gene expression and motif finding. Interestingly, it is attempted to introduce computational biology without formulas that presents the biological and computational ideas in a relatively simple manner. It focuses on computational and statistical principles applied to genomes, and introduces the computational statistics that are crucial for understanding and visualization of problems. This makes the material accessible to Statistician and computer scientists without biological training, as well as to biologists with limited background in Statistics and computer science. Furthermore one chapter has been exclusively devoted to computational biology and computational statistics as applied in biotechnology illustrated with methodology, application and interpretation of results. More than four hundred figures, illustrations and diagrams reinforce concepts and present key results from the primary literature that will be very much useful to grasp on the subject, visualize the output and make right interpretation of the result. The book will be useful for all those working in Biotechnology sector in general and particularly researchers working in the laboratories of ICAR, CSIR, SAU's and many more institutions engaged R&D activities.

Statistics for Bioinformatics

Statistics for Bioinformatics Book
Author : Julie Thompson
Publisher : Elsevier
Release : 2016-11-24
ISBN : 0081019610
Language : En, Es, Fr & De

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Book Description :

Statistics for Bioinformatics: Methods for Multiple Sequence Alignment provides an in-depth introduction to the most widely used methods and software in the bioinformatics field. With the ever increasing flood of sequence information from genome sequencing projects, multiple sequence alignment has become one of the cornerstones of bioinformatics. Multiple sequence alignments are crucial for genome annotation, as well as the subsequent structural, functional, and evolutionary studies of genes and gene products. Consequently, there has been renewed interest in the development of novel multiple sequence alignment algorithms and more efficient programs. Explains the dynamics that animate health systems Explores tracks to build sustainable and equal architecture of health systems Examines the advantages and disadvantages of the different approaches to care integration and the management of health information

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques Tools and Applications

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques  Tools  and Applications Book
Author : K. G. Srinivasa,G. M. Siddesh,S. R. Manisekhar
Publisher : Springer Nature
Release : 2020-01-30
ISBN : 9811524459
Language : En, Es, Fr & De

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Book Description :

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

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.

Applied Statistics for Bioinformatics Using R

Applied Statistics for Bioinformatics Using R Book
Author : Anonim
Publisher : Unknown
Release : 2021-07-30
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Applied Statistics for Bioinformatics Using R book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics Book
Author : Dipak K. Dey,Samiran Ghosh,Bani K. Mallick
Publisher : CRC Press
Release : 2010-09-03
ISBN : 1420070185
Language : En, Es, Fr & De

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Book Description :

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and c

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.

Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Bioinformatics and Computational Biology Solutions Using R and Bioconductor Book
Author : Robert Gentleman,Vincent Carey,Wolfgang Huber,Rafael Irizarry,Sandrine Dudoit
Publisher : Springer Science & Business Media
Release : 2006-01-27
ISBN : 0387293620
Language : En, Es, Fr & De

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Book Description :

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

Handbook of Statistical Bioinformatics

Handbook of Statistical Bioinformatics Book
Author : Henry Horng-Shing Lu,Bernhard Schölkopf,Hongyu Zhao
Publisher : Springer Science & Business Media
Release : 2011-05-17
ISBN : 9783642163456
Language : En, Es, Fr & De

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Book Description :

Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.

Basics of Bioinformatics

Basics of Bioinformatics Book
Author : Rui Jiang,Xuegong Zhang,Michael Q. Zhang
Publisher : Springer Science & Business Media
Release : 2013-11-26
ISBN : 3642389511
Language : En, Es, Fr & De

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Book Description :

This book outlines 11 courses and 15 research topics in bioinformatics, based on curriculums and talks in a graduate summer school on bioinformatics that was held in Tsinghua University. The courses include: Basics for Bioinformatics, Basic Statistics for Bioinformatics, Topics in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics Research, Association Analysis for Human Diseases: Methods and Examples, Data Mining and Knowledge Discovery Methods with Case Examples, Applied Bioinformatics Tools, Foundations for the Study of Structure and Function of Proteins, Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine, and Advanced Topics in Bioinformatics and Computational Biology. This book can serve as not only a primer for beginners in bioinformatics, but also a highly summarized yet systematic reference book for researchers in this field. Rui Jiang and Xuegong Zhang are both professors at the Department of Automation, Tsinghua University, China. Professor Michael Q. Zhang works at the Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.

Statistical Bioinformatics

Statistical Bioinformatics Book
Author : Jae K. Lee
Publisher : John Wiley & Sons
Release : 2011-09-20
ISBN : 1118211529
Language : En, Es, Fr & De

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Book Description :

This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into topics such as clustering, classification, multi-dimensional visualization, experimental design, statistical resampling, and statistical network analysis. Clearly explains the use of bioinformatics tools in life sciences research without requiring an advanced background in math/statistics Enables biomedical and life sciences researchers to successfully evaluate the validity of their results and make inferences Enables statistical and quantitative researchers to rapidly learn novel statistical concepts and techniques appropriate for large biological data analysis Carefully revisits frequently used statistical approaches and highlights their limitations in large biological data analysis Offers programming examples and datasets Includes chapter problem sets, a glossary, a list of statistical notations, and appendices with references to background mathematical and technical material Features supplementary materials, including datasets, links, and a statistical package available online Statistical Bioinformatics is an ideal textbook for students in medicine, life sciences, and bioengineering, aimed at researchers who utilize computational tools for the analysis of genomic, proteomic, and many other emerging high-throughput molecular data. It may also serve as a rapid introduction to the bioinformatics science for statistical and computational students and audiences who have not experienced such analysis tasks before.

New Frontiers of Biostatistics and Bioinformatics

New Frontiers of Biostatistics and Bioinformatics Book
Author : Yichuan Zhao,Ding-Geng Chen
Publisher : Springer
Release : 2019-02-03
ISBN : 9783319993881
Language : En, Es, Fr & De

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Book Description :

This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas. Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners.

Statistical Bioinformatics with R

Statistical Bioinformatics with R Book
Author : Sunil K. Mathur
Publisher : Academic Press
Release : 2009-12-21
ISBN : 9780123751058
Language : En, Es, Fr & De

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Book Description :

Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications. Designed for a one or two semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications. The inclusion of R & SAS code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics. Integrates biological, statistical and computational concepts Inclusion of R & SAS code Provides coverage of complex statistical methods in context with applications in bioinformatics Exercises and examples aid teaching and learning presented at the right level Bayesian methods and the modern multiple testing principles in one convenient book

Bioinformatics Computing

Bioinformatics Computing Book
Author : Bryan P. Bergeron
Publisher : Prentice Hall Professional
Release : 2003
ISBN : 9780131008250
Language : En, Es, Fr & De

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Book Description :

Comprehensive and concise, this handbook has chapters on computing visualization, large database designs, advanced pattern matching and other key bioinformatics techniques. It is a practical guide to computing in the growing field of Bioinformatics--the study of how information is represented and transmitted in biological systems, starting at the molecular level.

Scan Statistics

Scan Statistics Book
Author : Joseph Glaz,Vladimir Pozdnyakov,Sylvan Wallenstein
Publisher : Springer Science & Business Media
Release : 2009-12-24
ISBN : 9780817647490
Language : En, Es, Fr & De

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Book Description :

Scan statistics is currently one of the most active and important areas of research in applied probability and statistics, having applications to a wide variety of fields: archaeology, astronomy, bioinformatics, biosurveillance, molecular biology, genetics, computer science, electrical engineering, geography, material sciences, physics, reconnaissance, reliability and quality control, telecommunication, and epidemiology. Filling a gap in the literature, this self-contained volume brings together a collection of selected chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.

Statistics Applied to Bioinformatics

Statistics Applied to Bioinformatics Book
Author : Jacques Van Helden
Publisher : Oxford University Press, USA
Release : 2015-03-15
ISBN : 9780199226764
Language : En, Es, Fr & De

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Book Description :

A text based on the author's Masters level course on statistics applied to bioinformatics aimed at graduate students from statistics, bioinformatics and biology. Filling a gap in the current literature, the text includes a rigorous and extensive background in biostatistics, along with detailed explanation of the key biological questions before focusing on the statistical analysis. Including exercises, numerous illustrations, extensive end of chapter summaries and examples of programming in R (a freely availabe statistical package), this is an ideal study text.