Rna Seq Data Analysis

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Computational Genomics with R

Author : Altuna Akalin
Publisher : CRC Press
Page : 462 pages
File Size : 46,8 Mb
Release : 2020-12-16
Category : Mathematics
ISBN : 9781498781862

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Computational Genomics with R by Altuna Akalin Pdf

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

RNA-seq Data Analysis

Author : Eija Korpelainen,Jarno Tuimala,Panu Somervuo,Mikael Huss,Garry Wong
Publisher : CRC Press
Page : 322 pages
File Size : 51,9 Mb
Release : 2014-09-19
Category : Mathematics
ISBN : 9781466595019

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RNA-seq Data Analysis by Eija Korpelainen,Jarno Tuimala,Panu Somervuo,Mikael Huss,Garry Wong Pdf

The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le

RNA Bioinformatics

Author : Ernesto Picardi
Publisher : Humana
Page : 0 pages
File Size : 46,9 Mb
Release : 2016-09-24
Category : Science
ISBN : 1493946447

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RNA Bioinformatics by Ernesto Picardi Pdf

This volume provides an overview of RNA bioinformatics methodologies, including basic strategies to predict secondary and tertiary structures, and novel algorithms based on massive RNA sequencing. Interest in RNA bioinformatics has rapidly increased thanks to the recent high-throughput sequencing technologies allowing scientists to investigate complete transcriptomes at single nucleotide resolution. Adopting advanced computational technics, scientists are now able to conduct more in-depth studies and present them to you in this book. Written in the highly successful Methods of Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and equipment, step-by-step, readily reproducible bioinformatics protocols, and key tips to avoid known pitfalls. Authoritative and practical, RNA Bioinformatics seeks to aid scientists in the further study of bioinformatics and computational biology of RNA.

Fusarium wilt

Author : Jeffrey Coleman
Publisher : Humana
Page : 0 pages
File Size : 46,9 Mb
Release : 2022-10-24
Category : Science
ISBN : 1071617974

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Fusarium wilt by Jeffrey Coleman Pdf

This volume provides a collection of molecular protocols detailing the most common and modern techniques on fusarium wilt. Chapters guide readers through methods on initial isolation, molecular-based identification, genome characterization, generation of mutants, and characterization of interactions with other organisms including host plants. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Fusarium wilt: Methods and Protocols aims to be a valuable resource for mycologists, plant pathologists, microbiologists, geneticists, and other scientists that have an interest in members of the Fusarium oxysporum species complex or closely related fungi.

RNA-Seq Analysis: Methods, Applications and Challenges

Author : Filippo Geraci,Indrajit Saha,Monica Bianchini
Publisher : Frontiers Media SA
Page : 169 pages
File Size : 48,8 Mb
Release : 2020-06-08
Category : Electronic
ISBN : 9782889637058

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RNA-Seq Analysis: Methods, Applications and Challenges by Filippo Geraci,Indrajit Saha,Monica Bianchini Pdf

Next-Generation Sequencing Data Analysis

Author : Xinkun Wang
Publisher : CRC Press
Page : 258 pages
File Size : 43,5 Mb
Release : 2016-04-06
Category : Mathematics
ISBN : 9781482217896

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Next-Generation Sequencing Data Analysis by Xinkun Wang Pdf

A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphi

Statistical Analysis of Next Generation Sequencing Data

Author : Somnath Datta,Dan Nettleton
Publisher : Springer
Page : 438 pages
File Size : 46,8 Mb
Release : 2014-07-03
Category : Medical
ISBN : 9783319072128

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Statistical Analysis of Next Generation Sequencing Data by Somnath Datta,Dan Nettleton Pdf

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.

Transcriptome Data Analysis

Author : Yejun Wang,Ming-an Sun
Publisher : Humana
Page : 238 pages
File Size : 50,5 Mb
Release : 2019-03-20
Category : Medical
ISBN : 1493992643

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Transcriptome Data Analysis by Yejun Wang,Ming-an Sun Pdf

This detailed volume provides comprehensive practical guidance on transcriptome data analysis for a variety of scientific purposes. Beginning with general protocols, the collection moves on to explore protocols for gene characterization analysis with RNA-seq data as well as protocols on several new applications of transcriptome studies. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and useful, Transcriptome Data Analysis: Methods and Protocols serves as an ideal guide to the expanding purposes of this field of study.

Computational Methods for Single-Cell Data Analysis

Author : Guo-Cheng Yuan
Publisher : Humana Press
Page : 271 pages
File Size : 55,8 Mb
Release : 2019-02-14
Category : Science
ISBN : 149399056X

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Computational Methods for Single-Cell Data Analysis by Guo-Cheng Yuan Pdf

This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.

Applications of RNA-Seq and Omics Strategies

Author : Fabio Marchi,Priscila Cirillo,Elvis Cueva Mateo
Publisher : BoD – Books on Demand
Page : 330 pages
File Size : 51,6 Mb
Release : 2017-09-13
Category : Medical
ISBN : 9789535135036

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Applications of RNA-Seq and Omics Strategies by Fabio Marchi,Priscila Cirillo,Elvis Cueva Mateo Pdf

The large potential of RNA sequencing and other "omics" techniques has contributed to the production of a huge amount of data pursuing to answer many different questions that surround the science's great unknowns. This book presents an overview about powerful and cost-efficient methods for a comprehensive analysis of RNA-Seq data, introducing and revising advanced concepts in data analysis using the most current algorithms. A holistic view about the entire context where transcriptome is inserted is also discussed here encompassing biological areas with remarkable technological advances in the study of systems biology, from microorganisms to precision medicine.

Deep Sequencing Data Analysis

Author : Noam Shomron
Publisher : Humana Press
Page : 0 pages
File Size : 47,5 Mb
Release : 2013-07-20
Category : Science
ISBN : 1627035133

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Deep Sequencing Data Analysis by Noam Shomron Pdf

The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), and various approaches for the identification of sequence variants. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation.

Plant Germline Development

Author : Anja Schmidt
Publisher : Humana
Page : 0 pages
File Size : 44,9 Mb
Release : 2018-08-11
Category : Science
ISBN : 149398442X

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Plant Germline Development by Anja Schmidt Pdf

This detailed volume explores common and numerous specialized methods to study various aspects of plant germline development and targeted manipulation, including imaging and hybridization techniques to study cell-type specification, cell lineage, signaling and hormones, cell cycle, and the cytoskeleton. In addition, cell-type specific methods for targeted ablation or isolation are provided, protocols to apply “omics” technologies and to perform bioinformatics data analysis, as well as methods relevant for aspects of biotechnology or plant breeding. This includes protocols that are relevant for the targeted manipulation of pathways, for crop plant transformation, or for conditional induction of phenotypes. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Plant Germline Development: Methods and Protocols serves as a comprehensive guide not only to studying basic questions related to different aspects of plant reproductive development but also for state of the art methods, in addition to being a source of inspiration for new approaches and research questions in many laboratories.

Practical Guide to ChIP-seq Data Analysis

Author : Borbala Mifsud,Kathi Zarnack,Anaïs F Bardet
Publisher : CRC Press
Page : 100 pages
File Size : 40,7 Mb
Release : 2018-10-26
Category : Computers
ISBN : 9780429946394

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Practical Guide to ChIP-seq Data Analysis by Borbala Mifsud,Kathi Zarnack,Anaïs F Bardet Pdf

Chromatin immunoprecipitation sequencing (ChIP-seq), which maps the genome-wide localization patterns of transcription factors and epigenetic marks, is among the most widely used methods in molecular biology. Practical Guide to ChIP-seq Data Analysis will guide readers through the steps of ChIP-seq analysis: from quality control, through peak calling, to downstream analyses. It will help experimental biologists to design their ChIP-seq experiments with the analysis in mind, and to perform the basic analysis steps themselves. It also aims to support bioinformaticians to understand how the data is generated, what the sources of biases are, and which methods are appropriate for different analyses.

Molecular Data Analysis Using R

Author : Csaba Ortutay,Zsuzsanna Ortutay
Publisher : John Wiley & Sons
Page : 354 pages
File Size : 45,9 Mb
Release : 2017-02-06
Category : Medical
ISBN : 9781119165026

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Molecular Data Analysis Using R by Csaba Ortutay,Zsuzsanna Ortutay Pdf

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.

Next Generation Sequencing

Author : Jerzy Kulski
Publisher : BoD – Books on Demand
Page : 466 pages
File Size : 41,7 Mb
Release : 2016-01-14
Category : Medical
ISBN : 9789535122401

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Next Generation Sequencing by Jerzy Kulski Pdf

Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences.