Bioinformatics for DNA Sequence Analysis
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Beschreibung
The storage, processing, description, transmission, connection, and analysis of the waves of new genomic data have made bioinformatics skills essential for scientists working with DNA sequences. In Bioinformatics for DNA Sequence Analysis, experts in the field provide practical guidance and troubleshooting advice for the computational analysis of DNA sequences, covering a range of issues and methods that unveil the multitude of applications and the vital relevance that the use of bioinformatics has today. Individual book chapters explore the use of specific bioinformatic tools, accompanied by practical examples, a discussion on the interpretation of results, and specific comments on strengths and limitations of the methods and tools. As a part of the highly successful Methods in Molecular Biology™ series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results.
Focused and cutting-edge, Bioinformatics for DNA Sequence Analysis serves molecular biologists, geneticists, and biochemists as an enriched task-oriented manual, offering step-by-step guidance for the analysis of DNA sequences in a simple but meaningful fashion.
The recent accumulation of information from genomes, including their sequences, has resultednotonlyinnewattemptstoansweroldquestionsandsolvelongstandingissues inbiology,butalsointheformulationofnovelhypothesesthatarisepreciselyfromthis wealth of data. The storage, processing, description, transmission, connection, and analysis of these data has prompted bioinformatics to become one the most relevant applied sciences for this new century, walking hand-in-hand with modern molecular biology and clearly impacting areas like biotechnology and biomedicine. Bioinformatics skills have now become essential for many scientists working with DNA sequences. With this idea in mind, this book aims to provide practical guidance andtroubleshootingadviceforthecomputationalanalysisofDNAsequences,covering a range of issues and methods that unveil the multitude of applications and relevance that Bioinformatics has today. The analysis of protein sequences has been purposely excludedtogainfocus.Individualbookchaptersareorientedtowardthedescriptionof theuseofspecificbioinformaticstools,accompaniedbypracticalexamples,adiscussion on the interpretation of results, and specific comments on strengths and limitations of the methods and tools. In a sense, chapters could be seen as enriched task-oriented manuals that will direct the reader in completing specific bioinformatics analyses. The target audience for this book is biochemists, and molecular and evolutionary biologiststhatwanttolearnhowtoanalyzeDNAsequencesinasimplebutmeaningful fashion. Readers do not need a special background in statistics, mathematics, or computer science, just a basic knowledge of molecular biology and genetics. All the tools described in the book are free and all of them can be downloaded or accessed throughtheweb.Mostchapterscouldbeusedforpracticaladvancedundergraduateor graduate-level courses in bioinformatics and molecular evolution.
Provides practical guidance and troubleshooting advice for the computational analysis of DNA sequences Covers a wide range of methods that unveil the multitude of applications and relevance of bioinformatics today Includes worked examples with real data that will direct the reader in completing specific bionformatic analyses Does not require a special background in statistics, mathematics or computer science, only a basic knowledge of molecular biology and genetics Describes only tools which are free and can be downloaded or accessed through the web Most chapters could be used for practical advanced undergraduate or graduate-level courses in bioinformatics and molecular evolution Includes supplementary material: sn.pub/extras
Autor*in
David Posada
Themen in »Bioinformatics for DNA Sequence Analysis«
Annotation BLAST-Algorithmus Bioinformatic tools Computational analysis Computer science DNA Data Promoter SNP Statistics and mathematics bioinformatics genes genome sequence analysis