Modern Statistics for Modern Biology Book

Modern Statistics for Modern Biology


  • Author : Susan Holmes
  • Publisher : Cambridge University Press
  • Release Date : 2018-11-30
  • Genre: Uncategoriezed
  • Pages : 400
  • ISBN 10 : 9781108427029

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Modern Statistics for Modern Biology Excerpt :

A far-reaching course in practical advanced statistics for biologists using R/Bioconductor, data exploration, and simulation.

Statistical Bioinformatics Book

Statistical Bioinformatics


  • Author : Jae K. Lee
  • Publisher : John Wiley & Sons
  • Release Date : 2011-09-20
  • Genre: Medical
  • Pages : 364
  • ISBN 10 : 9781118211526

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Statistical Bioinformatics Excerpt :

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 expe

Statistical Methods in Bioinformatics Book

Statistical Methods in Bioinformatics


  • Author : Warren J. Ewens
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-03-30
  • Genre: Science
  • Pages : 598
  • ISBN 10 : 9780387266480

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Statistical Methods in Bioinformatics Excerpt :

Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspe

Statistics for Bioinformatics Book

Statistics for Bioinformatics


  • Author : Julie Thompson
  • Publisher : Elsevier
  • Release Date : 2016-11-24
  • Genre: Medical
  • Pages : 146
  • ISBN 10 : 9780081019610

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Statistics for Bioinformatics Excerpt :

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

Handbook of Statistical Bioinformatics Book

Handbook of Statistical Bioinformatics


  • Author : Henry Horng-Shing Lu
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-05-17
  • Genre: Mathematics
  • Pages : 630
  • ISBN 10 : 9783642163456

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Handbook of Statistical Bioinformatics Excerpt :

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.

Statistical Bioinformatics with R Book

Statistical Bioinformatics with R


  • Author : Sunil K. Mathur
  • Publisher : Academic Press
  • Release Date : 2009-12-21
  • Genre: Mathematics
  • Pages : 336
  • ISBN 10 : 0123751055

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Statistical Bioinformatics with R Excerpt :

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

New Frontiers of Biostatistics and Bioinformatics Book

New Frontiers of Biostatistics and Bioinformatics


  • Author : Yichuan Zhao
  • Publisher : Springer
  • Release Date : 2018-12-05
  • Genre: Mathematics
  • Pages : 463
  • ISBN 10 : 9783319993898

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New Frontiers of Biostatistics and Bioinformatics Excerpt :

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

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


  • Author : K. G. Srinivasa
  • Publisher : Springer Nature
  • Release Date : 2020-01-30
  • Genre: Technology & Engineering
  • Pages : 317
  • ISBN 10 : 9789811524455

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

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 Modelling in Biostatistics and Bioinformatics Book

Statistical Modelling in Biostatistics and Bioinformatics


  • Author : Gilbert MacKenzie
  • Publisher : Springer Science & Business Media
  • Release Date : 2014-05-08
  • Genre: Mathematics
  • Pages : 244
  • ISBN 10 : 9783319045795

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Statistical Modelling in Biostatistics and Bioinformatics Excerpt :

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.

Bioinformatics and Computational Biology Solutions Using R and Bioconductor Book

Bioinformatics and Computational Biology Solutions Using R and Bioconductor


  • Author : Robert Gentleman
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-01-27
  • Genre: Computers
  • Pages : 474
  • ISBN 10 : 9780387293622

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Bioinformatics and Computational Biology Solutions Using R and Bioconductor Excerpt :

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.

Advances in Statistical Bioinformatics Book

Advances in Statistical Bioinformatics


  • Author : Kim-Anh Do
  • Publisher : Cambridge University Press
  • Release Date : 2013-06-10
  • Genre: Mathematics
  • Pages : 514
  • ISBN 10 : 9781107027527

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Advances in Statistical Bioinformatics Excerpt :

"Chapter 1 An introduction to next-generation biological platforms Virginia Mohlere, Wenting Wang, and Ganiraju Manyam The University of Texas. MD Anderson Cancer Center 1.1 Introduction When Sanger and Coulson first described a reliable, efficient method for DNA sequencing in 1975 (Sanger and Coulson, 1975), they made possible the full sequencing of both genes and entire genomes. Although the method was resource-intensive, many institutions invested in the necessary equipment, and Sanger sequencing remained the standard for the next 30 years. Refinement of the process increased read lengths from around 25 to 2 Mohlere, Wang, and Manyam almost 750 base pairs (Schadt et al., 2010, fig. 1). While this greatly increased efficiency and reliability, the Sanger method still required not only large equipment but significant human investment, as the process requires the work of several people. This prompted researchers and companies such as Applied Biosystems to seek improved sequencing techniques and instruments. Starting in the late 2000s, new instruments came on the market that, although they actually decreased read length, lessened run time and could be operated more easily with fewer human resources (Schadt et al., 2010). Despite discoveries that have illuminated new therapeutic targets, clarified the role of specific mutations in clinical response, and yielded new methods for diagnosis and predicting prognosis (Chin et al., 2011), the initial promise of genomic data has largely remained so far unfulfilled. The difficulties are numerous"--

R Programming for Bioinformatics Book

R Programming for Bioinformatics


  • Author : Robert Gentleman
  • Publisher : CRC Press
  • Release Date : 2008-07-14
  • Genre: Mathematics
  • Pages : 328
  • ISBN 10 : 1420063685

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R Programming for Bioinformatics Excerpt :

Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Programming for Bioinformatics explores the programming skills needed to use this software tool for the solution of bioinformatics and computational biology problems. Drawing on the author’s first-hand experiences as an expert in R, the book begins with coverage on the general properties of the R language, several unique programming aspects of R, and object-oriented programming in R. It presents methods for data input and output as well as database interactions. The author also examines different facets of string handling and manipulations, discusses the interfacing of R with other languages, and describes how to write software packages. He concludes with a discussion on the debugging and profiling of R code. With numerous examples and exercises, this practical guide focuses on developing R programming skills in order to tackle problems encountered in bioinformatics and computational biology.

Foundational and Applied Statistics for Biologists Using R Book

Foundational and Applied Statistics for Biologists Using R


  • Author : Ken A. Aho
  • Publisher : CRC Press
  • Release Date : 2016-03-09
  • Genre: Mathematics
  • Pages : 618
  • ISBN 10 : 9781439873397

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Foundational and Applied Statistics for Biologists Using R Excerpt :

Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complica

Statistical Advances in the Biomedical Sciences Book

Statistical Advances in the Biomedical Sciences


  • Author : Atanu Biswas
  • Publisher : John Wiley & Sons
  • Release Date : 2007-12-14
  • Genre: Mathematics
  • Pages : 616
  • ISBN 10 : 0470181192

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Statistical Advances in the Biomedical Sciences Excerpt :

The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research and the sophisticated advances in computing, it has become essential for practitioners in the biomedical sciences to be fully educated on the role statistics plays in ensuring the accurate analysis of research findings. Statistical Advances in the Biomedical Sciences explores the growing value of statistical knowledge in the management and comprehension of medical research and, more specifically, provides an accessible introduction to the contemporary methodologies used to understand complex problems in the four major areas of modern-day biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Composed of contributions from eminent researchers in the field, this volume discusses the application of statistical techniques to various aspects of modern medical research and illustrates how these methods ultimately prove to be an indispensable part of proper data collection and analysis. A structural uniformity is maintained across all chapters, each beginning with an introduction that discusses general concepts and the biomedical problem under focus and is followed by specific details on the associated methods, algorithms, and applications. In addition, each chapter provides a summary of the main ideas and offers a concluding remarks section that presents novel ideas, approaches, and challenges for future research. Complete with detailed references and insight on the future directions of biomedical research, Statistical Advances in the Biomedical Sciences provides vital statistical guidance to practitioners in the biomedical sciences while also introducing statisticians to new, multidisciplinary frontiers of application. This text is an excellent reference for graduate- and PhD-level courses in various areas of biostatistics and the medical sciences and also serves as a valuable tool

Bayesian Modeling in Bioinformatics Book

Bayesian Modeling in Bioinformatics


  • Author : Dipak K. Dey
  • Publisher : CRC Press
  • Release Date : 2010-09-03
  • Genre: Mathematics
  • Pages : 466
  • ISBN 10 : 9781420070187

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Bayesian Modeling in Bioinformatics Excerpt :

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