data analysis visualization genomics (10 Ergebnisse)

Taschenbuch. Zustand: Neu. R Bioinformatics Cookbook | Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis | Dan Maclean | Taschenbuch | Kartoniert / Broschiert | Englisch | 2019 | Packt Publishing | EAN 9781789950694 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Neuware - Over 60 recipes to model and handle real-life biological data using modern libraries from the R ecosystemKey Features:Apply modern R packages to handle biological data using real-world examplesRepresent biological data with advanced visualizations suitable for research and publicationsHandle real-world problems in bioinformatics such as next-generation sequencing, metagenomics, and automating analysesBook Description:Handling biological data effectively requires an in-depth knowledge of machine learning techniques and computational skills, along with an understanding of how to use tools such as edgeR and DESeq. With the R Bioinformatics Cookbook, you'll explore all this and more, tackling common and not-so-common challenges in the bioinformatics domain using real-world examples.This book will use a recipe-based approach to show you how to perform practical research and analysis in computational biology with R. You will learn how to effectively analyze your data with the latest tools in Bioconductor, ggplot, and tidyverse. The book will guide you through the essential tools in Bioconductor to help you understand and carry out protocols in RNAseq, phylogenetics, genomics, and sequence analysis. As you progress, you will get up to speed with how machine learning techniques can be used in the bioinformatics domain. You will gradually develop key computational skills such as creating reusable workflows in R Markdown and packages for code reuse.By the end of this book, you'll have gained a solid understanding of the most important and widely used techniques in bioinformatic analysis and the tools you need to work with real biological data.What You Will Learn:Employ Bioconductor to determine differential expressions in RNAseq dataRun SAMtools and develop pipelines to find single nucleotide polymorphisms (SNPs) and IndelsUse ggplot to create and annotate a range of visualizationsQuery external databases with Ensembl to find functional genomics informationExecute large-scale multiple sequence alignment with DECIPHER to perform comparative genomicsUse d3.js and Plotly to create dynamic and interactive web graphicsUse k-nearest neighbors, support vector machines and random forests to find groups and classify dataWho this book is for:¿This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate-to-advanced biological and bioinformatics problems by learning through a recipe-based approach. Working knowledge of R programming language and basic knowledge of bioinformatics are prerequisites.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 284 | Sprache: Englisch | Produktart: Bücher | This book provides scientists and students with the basis for the development of integrative computational approaches to analysing biological data on a systemic scale.  It emphasises the processing of multiple data and knowledge resources, and the combination of different prediction models and systems. It covers different data analysis and visualisation techniques for studying the roles of genes and proteins at a systems level. A fairly broad definition for the areas of genomics and proteomics is adopted, which also encompasses a wider spectrum of 'omic' approaches required to understand the functions of genes and their products. From a bioinformatics point of view, the book illustrates: how data analysis techniques can facilitate more comprehensive, user-friendly data visualisation tasks; how data visualisation methods may make data analysis a more meaningful and biologically relevant process; and how to approach the overabundance of data in genomic studies, in which spurious associations often occur, with the proper statistical tools. The book describes how this synergy may support integrative approaches to functional genomics. The book will be of interest to all bioinformaticians, from students to researchers, as well as to many scientists working in genomics, proteomics, systems biology and related areas.

1. 284 p. Very good condition. Reading pages are very clean and without marks. Slight traces of storage or use. Otherwise very good exemplar. 9780470094396 Sprache: Englisch Gewicht in Gramm: 699 Hardcover: 15.6 x 2.4 x 25.3 cm.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

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Gebunden. Zustand: New. This book provides scientists and students with the basis for the development of integrative computational approaches to analysing biological data on a systemic scale. It emphasises the processing of multiple data and knowledge resources, and the combinatio.

Hardcover. Zustand: Brand New. 1st edition. 267 pages. 9.50x6.50x0.75 inches. In Stock.

Zustand: New. Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. Editor(s): Azuaje, Francisco; Dopazo, Joaquin. Num Pages: 284 pages, Illustrations. BIC Classification: UNC. Category: (P) Professional & Vocational. Dimension: 249 x 177 x 22. Weight in Grams: 650. . 2005. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems.\* One of the first systematic overviews of the problem of biological data integration using computational approaches\* This book provides scientists and students with the basis for the development and application of integrative computational methods to analyse biological data on a systemic scale\* Places emphasis on the processing of multiple data and knowledge resources, and the combination of different models and systems.