Modern Statistics for Modern Biology

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  • Publisher : Cambridge University Press
  • Release : 30 November 2018
  • ISBN : 9781108427029
  • Page : 400 pages
  • Rating : 4.5/5 from 103 voters

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

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Modern Statistics for Modern Biology

Modern Statistics for Modern Biology
  • Author : Susan Holmes,Wolfgang Huber
  • Publisher : Cambridge University Press
  • Release Date : 2018-11-30
  • ISBN : 9781108427029
GET THIS BOOKModern Statistics for Modern Biology

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

Statistical Bioinformatics

Statistical Bioinformatics
  • Author : Jae K. Lee
  • Publisher : John Wiley & Sons
  • Release Date : 2011-09-20
  • ISBN : 9781118211526
GET THIS BOOKStatistical Bioinformatics

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 Bioinformatics

Statistics for Bioinformatics
  • Author : Julie Thompson
  • Publisher : Elsevier
  • Release Date : 2016-11-24
  • ISBN : 9780081019610
GET THIS BOOKStatistics for Bioinformatics

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

Statistical Methods in Bioinformatics

Statistical Methods in Bioinformatics
  • Author : Warren J. Ewens,Gregory R. Grant
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-03-30
  • ISBN : 9780387266480
GET THIS BOOKStatistical Methods in Bioinformatics

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

Handbook of Statistical Bioinformatics

Handbook of Statistical Bioinformatics
  • Author : Henry Horng-Shing Lu,Bernhard Schölkopf,Hongyu Zhao
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-05-17
  • ISBN : 9783642163456
GET THIS BOOKHandbook of Statistical Bioinformatics

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

Statistical Bioinformatics with R

Statistical Bioinformatics with R
  • Author : Sunil K. Mathur
  • Publisher : Academic Press
  • Release Date : 2009-12-21
  • ISBN : 0123751055
GET THIS BOOKStatistical Bioinformatics with R

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

New Frontiers of Biostatistics and Bioinformatics

New Frontiers of Biostatistics and Bioinformatics
  • Author : Yichuan Zhao,Ding-Geng Chen
  • Publisher : Springer
  • Release Date : 2018-12-05
  • ISBN : 9783319993898
GET THIS BOOKNew Frontiers of Biostatistics and Bioinformatics

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

Bayesian Methods in Structural Bioinformatics

Bayesian Methods in Structural Bioinformatics
  • Author : Thomas Hamelryck,Kanti Mardia,Jesper Ferkinghoff-Borg
  • Publisher : Springer
  • Release Date : 2012-03-23
  • ISBN : 9783642272257
GET THIS BOOKBayesian Methods in Structural Bioinformatics

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

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

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications
  • Author : K. G. Srinivasa,G. M. Siddesh,S. R. Manisekhar
  • Publisher : Springer Nature
  • Release Date : 2020-01-30
  • ISBN : 9789811524455
GET THIS BOOKStatistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

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

Statistical Modelling in Biostatistics and Bioinformatics
  • Author : Gilbert MacKenzie,Defen Peng
  • Publisher : Springer Science & Business Media
  • Release Date : 2014-05-08
  • ISBN : 9783319045795
GET THIS BOOKStatistical Modelling in Biostatistics and Bioinformatics

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

Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Bioinformatics and Computational Biology Solutions Using R and Bioconductor
  • Author : Robert Gentleman,Vincent Carey,Wolfgang Huber,Rafael Irizarry,Sandrine Dudoit
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-01-27
  • ISBN : 9780387293622
GET THIS BOOKBioinformatics and Computational Biology Solutions Using R and Bioconductor

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

Advances in Statistical Bioinformatics
  • Author : Kim-Anh Do,Steven Qin,Marina Vannucci
  • Publisher : Cambridge University Press
  • Release Date : 2013-06-10
  • ISBN : 9781107027527
GET THIS BOOKAdvances in Statistical Bioinformatics

"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

Foundational and Applied Statistics for Biologists Using R

Foundational and Applied Statistics for Biologists Using R
  • Author : Ken A. Aho
  • Publisher : CRC Press
  • Release Date : 2016-03-09
  • ISBN : 9781439873397
GET THIS BOOKFoundational and Applied Statistics for Biologists Using R

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

R Programming for Bioinformatics

R Programming for Bioinformatics
  • Author : Robert Gentleman
  • Publisher : CRC Press
  • Release Date : 2008-07-14
  • ISBN : 1420063685
GET THIS BOOKR Programming for Bioinformatics

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

Statistical Advances in the Biomedical Sciences

Statistical Advances in the Biomedical Sciences
  • Author : Atanu Biswas,Sujay Datta,Jason P. Fine,Mark R. Segal
  • Publisher : John Wiley & Sons
  • Release Date : 2007-12-14
  • ISBN : 0470181192
GET THIS BOOKStatistical Advances in the Biomedical Sciences

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