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

Modern Statistics for Modern Biology Book PDF summary

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
DOWNLOAD BOOKModern Statistics for Modern Biology

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

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
DOWNLOAD 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 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
DOWNLOAD 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

Statistical Bioinformatics

Statistical Bioinformatics
  • Author : Jae K. Lee
  • Publisher : John Wiley & Sons
  • Release Date : 2011-09-20
  • ISBN : 9781118211526
DOWNLOAD 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
DOWNLOAD 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 Bioinformatics with R

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

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
DOWNLOAD 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.

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
DOWNLOAD 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