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Statistics and Data Analysis for Microarrays Using R and Bioconductor

Statistics and Data Analysis for Microarrays Using R and Bioconductor
Author: Sorin Draghici
Publisher: CRC Press
Total Pages: 1036
Release: 2016-04-19
Genre: Computers
ISBN: 1439809763

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Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on,


Statistics and Data Analysis for Microarrays Using R and Bioconductor, 2nd Edition

Statistics and Data Analysis for Microarrays Using R and Bioconductor, 2nd Edition
Author: Sorin Draghici
Publisher:
Total Pages: 0
Release: 2016
Genre:
ISBN:

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Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on,


The Analysis of Gene Expression Data

The Analysis of Gene Expression Data
Author: Giovanni Parmigiani
Publisher: Springer Science & Business Media
Total Pages: 511
Release: 2006-04-11
Genre: Medical
ISBN: 0387216790

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This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.


Microarray Data

Microarray Data
Author: Shailaja R. Deshmukh
Publisher: Alpha Science International, Limited
Total Pages: 354
Release: 2007
Genre: Business & Economics
ISBN:

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Functional Genomics, a branch of bioinformatics, is essentially an interdisciplinary subject in which biologists, statisticians and computer experts interact to analyze the microarray data. This book caters to the needs of all the three disciplines. For biologists and computer scientists, it explains concepts of statistics and statistical inference. For Biologists and Statisticians, it provides annotated R programs to analyze microarray data. For Statisticians and Computer scientists, it explains basics of biology relevant to microarray experiment. Thus, the book will be useful to scientists from all the three disciplines, with not much knowledge of other disciplines, to analyze microarray data and interpret the results.


Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Author: Robert Gentleman
Publisher: Springer Science & Business Media
Total Pages: 478
Release: 2005-12-29
Genre: Computers
ISBN: 0387293620

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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.


Molecular Data Analysis Using R

Molecular Data Analysis Using R
Author: Csaba Ortutay
Publisher: John Wiley & Sons
Total Pages: 354
Release: 2017-02-06
Genre: Medical
ISBN: 1119165024

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This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.


Data Analysis for the Life Sciences with R

Data Analysis for the Life Sciences with R
Author: Rafael A. Irizarry
Publisher: CRC Press
Total Pages: 537
Release: 2016-10-04
Genre: Mathematics
ISBN: 1498775861

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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.


Statistics and Data Analysis for Microarrays using MATLAB , 2nd edition

Statistics and Data Analysis for Microarrays using MATLAB , 2nd edition
Author: Sorin Draghici
Publisher: Chapman and Hall/CRC
Total Pages: 706
Release: 2016-06-15
Genre: Science
ISBN: 9781439809778

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Bridging the gap between introductory theory and practical knowledge, this second edition reflects the fast-moving field of DNA microarrays by adding new and updated chapters that cover cutting-edge microarray topics. This edition now offers the option of learning elements of MATLAB® in parallel with data analysis. The author also includes Bioconductor tools that are linked to the theoretical concepts discussed in the text. This edition also features more opportunities for readers to practice everything that they have learned from the book. The accompanying CD-ROM provides MATLAB code and tips on how to use the MATLAB Bioinformatics toolbox.


Knowledge Exploration in Life Science Informatics

Knowledge Exploration in Life Science Informatics
Author: Jesús A. López
Publisher: Springer
Total Pages: 258
Release: 2005-01-27
Genre: Computers
ISBN: 3540304789

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This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.


Statistical Analysis of Gene Expression Microarray Data

Statistical Analysis of Gene Expression Microarray Data
Author: Terry Speed
Publisher: CRC Press
Total Pages: 237
Release: 2003-03-26
Genre: Mathematics
ISBN: 0203011236

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Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies