The Analysis of Biological Data

The Analysis of Biological Data
Author: Michael C. Whitlock
Publisher: Macmillan Higher Education
Total Pages: 2074
Release: 2019-11-22
Genre:
ISBN: 1319226299
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The Analysis of Biological Data provides students with a practical foundation of statistics for biology students. Every chapter has several biological or medical examples of key concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have dozens of practice problems based on real data. The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to qualified instructors (see below).

A Primer in Biological Data Analysis and Visualization Using R

A Primer in Biological Data Analysis and Visualization Using R
Author: Gregg Hartvigsen
Publisher: Columbia University Press
Total Pages: 245
Release: 2014-02-18
Genre: Education
ISBN: 0231537042
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.

Data Processing Handbook for Complex Biological Data Sources

Data Processing Handbook for Complex Biological Data Sources
Author: Gauri Misra
Publisher: Academic Press
Total Pages: 188
Release: 2019-03-23
Genre: Medical
ISBN: 0128172800
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Data Processing Handbook for Complex Biological Data provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened. Explains how to interpret enormous amounts of data generated using several experimental approaches in simple terms, thus relating biology and physics at the atomic level Presents sample data files and explains the usage of equations and web servers cited in research articles to extract useful information from their own biological data Discusses, in detail, raw data files, data processing strategies, and the web based sources relevant for data processing

Modern Analysis of Biological Data

Modern Analysis of Biological Data
Author: Stanislav Pekár
Publisher: Masarykova univerzita
Total Pages: 259
Release: 2016-01-01
Genre: Art
ISBN: 8021081066
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Kniha je zaměřena na regresní modely, konkrétně jednorozměrné zobecněné lineární modely (GLM). Je určena především studentům a kolegům z biologických oborů a vyžaduje pouze základní statistické vzdělání, jakým je např. jednosemestrový kurz biostatistiky. Text knihy obsahuje nezbytné minimum statistické teorie, především však řešení 18 reálných příkladů z oblasti biologie. Každý příklad je rozpracován od popisu a stanovení cíle přes vývoj statistického modelu až po závěr. K analýze dat je použit populární a volně dostupný statistický software R. Příklady byly záměrně vybrány tak, aby upozornily na leckteré problémy a chyby, které se mohou v průběhu analýzy dat vyskytnout. Zároveň mají čtenáře motivovat k tomu, jak o statistických modelech přemýšlet a jak je používat. Řešení příkladů si může čtenář vyzkoušet sám na datech, jež jsou dodávána spolu s knihou.

Biological Data Analysis

Biological Data Analysis
Author: John C. Fry
Publisher: IRL Press
Total Pages: 452
Release: 1993
Genre: Computers
ISBN:
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Many biologists remain unfamiliar with statistical analysis and modelling, yet need to apply these techniques increasingly in their research. This volume describes how to analyze biological data, with commonly available software packages, without making errors which can invalidate results. Practical guidance is provided for planning the correct strategy for a variety of different statistical approaches and modelling problems and interpreting the results. Many examples of computer commands and output are given to illustrate the different analytical approaches. Biological Data Analysis: A Practical Approach has been designed specifically to allow researchers with only a minimal knowledge of statistics to understand a variety of statistical methods and apply them directly. The provision of data sets from several biological disciplines will make this book useful to all types of biologists.

Analysis of Biological Networks

Analysis of Biological Networks
Author: Björn H. Junker
Publisher: John Wiley & Sons
Total Pages: 278
Release: 2011-09-20
Genre: Computers
ISBN: 1118209915
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An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.

Experimental Design and Data Analysis for Biologists

Experimental Design and Data Analysis for Biologists
Author: Gerald Peter Quinn
Publisher: Cambridge University Press
Total Pages: 560
Release: 2002-03-21
Genre: Mathematics
ISBN: 9780521009768
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Regression, analysis of variance, correlation, graphical.

Biological Sequence Analysis

Biological Sequence Analysis
Author: Richard Durbin
Publisher: Cambridge University Press
Total Pages: 372
Release: 1998-04-23
Genre: Science
ISBN: 113945739X
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Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Computational Intelligence and Pattern Analysis in Biology Informatics

Computational Intelligence and Pattern Analysis in Biology Informatics
Author: Ujjwal Maulik
Publisher: John Wiley & Sons
Total Pages: 552
Release: 2011-03-21
Genre: Medical
ISBN: 1118097807
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An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers Chapters authored by leading researchers in CI in biology informatics. Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases. Supplementary material included: program code and relevant data sets correspond to chapters.