Bioconductor Case Studies
Bioconductor Case Studies

Author: Florian Hahne

Publisher: Springer Science & Business Media

Published: 2010-06-09

Total Pages: 287

ISBN-13: 0387772405

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Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. Its application spans a broad field of technologies used in contemporary molecular biology. In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Topics covered include: (1) import and preprocessing of data from various sources; (2) statistical modeling of differential gene expression; (3) biological metadata; (4) application of graphs and graph rendering; (5) machine learning for clustering and classification problems; (6) gene set enrichment analysis. Each chapter of this book describes an analysis of real data using hands-on example driven approaches. Short exercises help in the learning process and invite more advanced considerations of key topics. The book is a dynamic document. All the code shown can be executed on a local computer, and readers are able to reproduce every computation, figure, and table.

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

Published: 2005-12-29

Total Pages: 478

ISBN-13: 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.

Omic Association Studies with R and Bioconductor
Omic Association Studies with R and Bioconductor

Author: Juan R. González

Publisher: CRC Press

Published: 2019-06-14

Total Pages: 356

ISBN-13: 0429803362

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After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies. Newcomers to the field are confronted with a wealth of data, resources and methods. This book presents current methods to perform informative analyses using real and illustrative data with established bioinformatics tools and guides the reader through the use of publicly available data. Includes clear, readable programming codes for readers to reproduce and adapt to their own data. Emphasises extracting biologically meaningful associations between traits of interest and genomic, transcriptomic and epigenomic data Uses up-to-date methods to exploit omic data Presents methods through specific examples and computing sessions Supplemented by a website, including code, datasets, and solutions

Computer Simulation and Data Analysis in Molecular Biology and Biophysics
Computer Simulation and Data Analysis in Molecular Biology and Biophysics

Author: Victor Bloomfield

Publisher: Springer Science & Business Media

Published: 2009-06-05

Total Pages: 325

ISBN-13: 1441900837

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This book provides an introduction to two important aspects of modern bioch- istry, molecular biology, and biophysics: computer simulation and data analysis. My aim is to introduce the tools that will enable students to learn and use some f- damental methods to construct quantitative models of biological mechanisms, both deterministicandwithsomeelementsofrandomness;tolearnhowconceptsofpr- ability can help to understand important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data. The availability of very capable but inexpensive personal computers and software makes it possible to do such work at a much higher level, but in a much easier way, than ever before. TheExecutiveSummaryofthein?uential2003reportfromtheNationalAcademy of Sciences, “BIO 2010: Transforming Undergraduate Education for Future - search Biologists” [12], begins The interplay of the recombinant DNA, instrumentation, and digital revolutions has p- foundly transformed biological research. The con?uence of these three innovations has led to important discoveries, such as the mapping of the human genome. How biologists design, perform, and analyze experiments is changing swiftly. Biological concepts and models are becoming more quantitative, and biological research has become critically dependent on concepts and methods drawn from other scienti?c disciplines. The connections between the biological sciences and the physical sciences, mathematics, and computer science are rapidly becoming deeper and more extensive.

Microarray Technology in Practice
Microarray Technology in Practice

Author: Steve Russell

Publisher: Academic Press

Published: 2008-11-21

Total Pages: 460

ISBN-13: 0080919766

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Using chips composed of thousands of spots, each with the capability of holding DNA molecules corresponding to a given gene, DNA microarray technology has enabled researchers to measure simultaneously gene expression across the genome. As with other large-scale genomics approaches, microarray technologies are broadly applicable across disciplines of life and biomedical sciences, but remain daunting to many researchers. This guide is designed to demystify the technology and inform more biologists about this critically important experimental technique. - Cohesive overview of the technology and available platforms, followed by detailed discussion of experimental design and analysis of microarray experiments - Up-to-date description of normalization methods and current methods for sample amplification and labeling - Deep focus on oligonucleotide design, printing, labeling and hybridization, data acquisition, normalization, and meta-analysis - Additional uses of microarray technology such as ChIP (chromatin immunoprecipitation) with hybridization to DNA arrays, microarray-based comparative genomic hybridization (CGH), and cell and tissue arrays

Statistical Bioinformatics
Statistical Bioinformatics

Author: Jae K. Lee

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 337

ISBN-13: 1118211529

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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 experienced such analysis tasks before.

Gene Expression Studies Using Affymetrix Microarrays
Gene Expression Studies Using Affymetrix Microarrays

Author: Hinrich Gohlmann

Publisher: CRC Press

Published: 2009-07-15

Total Pages: 361

ISBN-13: 1420065165

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The Affymetrix GeneChip system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a combined decade of

Introduction to Computational Genomics
Introduction to Computational Genomics

Author: Nello Cristianini

Publisher: Cambridge University Press

Published: 2006-12-14

Total Pages: 200

ISBN-13: 9780521856034

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Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.

Microarray Gene Expression Data Analysis
Microarray Gene Expression Data Analysis

Author: Helen Causton

Publisher: John Wiley & Sons

Published: 2009-04-01

Total Pages: 176

ISBN-13: 1444311565

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This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays

Bacterial Genomics
Bacterial Genomics

Author: Aswin Sai Narain Seshasayee

Publisher: Cambridge University Press

Published: 2015-03-05

Total Pages: 228

ISBN-13: 1316338738

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The study of bacterial genetics has revolutionised with the development of genome sequencing, which let us catalogue the gene content of various clinically and industrially important bacteria and opened up the field of comparative genomics. The research findings on bacterial genetics were further enhanced by the development of allied techniques that allowed interrogation of the interactions and functions of the many components of the genome. These developments accelerated with the widespread adoption of quantitative deep-sequencing approaches. This process allowed both comparative and functional genomics on an unprecedented scale by presenting powerful tools to investigate multiple layers of bacterial adaptation and evolution. This book presents the application of genomic tools to examine bacterial adaptation. The emphasis is on data analysis and interpretation. Much of the material is drawn from the recent, primary literature, which is the most powerful tool in the cutting-edge and fast-growing field of bacterial research.