
Plant Bioinformatics
Description
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The second edition of this volume focuses on applied bioinformatics with specific applications to crops and model plants. Plant Bioinformatics: Methods and Protocols is aimed at plant biologists who have an interest in, or requirement for, accessing and manipulating huge amounts of data being generated by high throughput technologies. This book would also be of interest to bioinformaticians and computer scientists who would benefit from an introduction to the different tools and systems available for plant research. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and software, step-by-step, readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and thorough, Plant Bioinformatics: Methods and Protocols helps researchers with the increasing volume and diversity of data from different plants and also the integration of multiple diverse forms of data.
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Content
Using GenBank.- UniProtKB/Swiss-Prot, The Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View.- KEGG Bioinformatics Resource for Plant Genomics and Metabolomics.- Plant Pathway Databases.- The Plant Ontology: A Tool for Plant Genomics.- Ensembl Plants: Integrating Tools for Visualizing, Mining, and Analyzing Plant Genomics Data.- Gramene: A Resource for Comparative Analysis of Plants Genomes and Pathways.- PGSB/MIPS Plant Genome Information Resources and Concepts for the Analysis of Complex Grass Genomes.- MaizeGDB: The Maize Genetics and Genomics Database.- WheatGenome.info: A Resource for Wheat Genomics Resource.- User Guidelines for the Brassica Database: BRAD.- TAG Sequence Identification of Genomic Regions Using TAGdb.- Short Read Alignment Using SOAP2.- Tablet: Visualizing Next-Generation Sequence Assemblies and Mappings.- Analysis of Genotyping-by-Sequencing (GBS) Data.- Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions and Improve Genome Assemblies.- Finding and Characterizing Repeats in Plant Genomes.- Analysis of RNA-Seq Data Using TopHat and Cufflinks.
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