| Description |
1 online resource (xiii, 217 pages) : illustrations |
| Contents |
A. Author's profile -- B. Dedication -- C. Preface -- D. Acknowledgements -- A. Part one: principles -- 1. Web-based sequence analysis: blast i -- Basic local alignment search tool (blast) -- The purpose of blast -- Terminology -- Blast analysis -- Blast2 -- Automated alignments with perl -- Assignments -- Appendix i -- References -- 2. Web-based sequence analysis: blast ii -- Basic local alignment search tool (blast) -- Scoring matrices -- Pam or per cent accepted mutation matrices -- Blosum (blocks substitution matrices) -- The relationship between blosum and pam substitution matrices -- Working of the blast algorithm -- A practical blastn exercise -- Explanation of the blast output -- Advanced blastn -- Biological analysis of blastn: cystic fibrosis -- Automating blast analyses with perl -- Assignments -- 3. Web-based sequence analysis: blast iii -- Standalone blast -- Configuring blastall -- Downloading databases from ncbi -- Formatting ncbi's databases -- Running blastall -- ̂Downloading pre-formatted databases -- Fastacmd -- Bl2seq -- Performing local blast searches with perl -- Sequence annotation -- Assignments -- 4. Web-based sequence analysis: gene prediction -- Introduction -- Terminology and concepts -- Gene prediction programs -- Genscan -- Running genscan analyses -- Analyzing genscan output -- Genscan analysis with lwp::useragent -- Assignments -- 5. Web-based sequence analysis: hmmer -- Introduction -- Downloading hmmer -- Why use hmmer? -- Running hmmer commands -- Hmmer: a practical example -- Hmmer utilities -- Assignments -- References -- 6. Psi-blast -- Introduction -- Psi-blast and protein analysis -- When is psi-blast better than blastp? -- The design of psi-blast -- Advantages of psi-blast -- Limitations of psi-blast -- Example of a psi-blast search -- Assignments -- B. Part two: applications -- 7. Accessing sequence information using bioperl -- Bioperl installation -- Bioperl modules -- Object oriented programming -- Using bioperl -- ̂The write_seq() function -- Assignments -- Appendix i: installing external modules -- Appendix ii: upgrading bioperl -- Appendix iii: testing for availability of individual modules -- 8. Bio::db::genbank -- Introduction -- Structure of a genbank record -- The bio::db::genbank module -- Assignments -- 9. Accessing genbank data -- Introduction -- Genbank tags -- Extracting tags and their values -- Sample scripts -- Assignments -- 10. Bioperl blast modules -- Introduction -- Blast programs -- Blast2 -- Perl modules for blast2 -- Using bioperl for blast2 -- Standalone blast -- Configuring blastall -- Bio::tools::run::standaloneblast -- Performing blast searches -- Formatting ncbi's databases -- Running blastall -- Running blast with bio::tools::run::standaloneblast -- Assignments -- 11. Parsing blast output -- Generating a raw blast report -- The bio::tools::blast module -- Parsing the hpr blast report -- Specifying a filter function -- Formatting parsing results into a table or html -- ̂Assignments |
| Summary |
The International Human Genome Project (IHGP), accomplished in 2003, was undoubtedly a giant step for mankind in the sequencing and assembly of the entire human genome. This event has fundamentally altered the manner in which we analyze biological systems, our approach to the many unsolved problems, and indeed, our attempt to unravel the closely held mysteries of evens the simplest of living organisms. However, deriving biological meaning from the raw stack of three billion bases of human DNA would not have been possible without the development of new algorithms for data mining and analysis. This book is about those fundamental tools and techniques that revolutionized biomedical research, and enable us today to perform biology in silico. The book uses an integrative approach to illustrate the use of these tools, and binds them together to create a coherent strategy to tackle the overwhelming problem of biological information overload. Divided into two parts, the book covers the core set of tools that have become indispensable to scientific discovery in the post-genome era, and also demonstrates how these tools can be integrated programmatically with BioPerl to be used in an enhanced, truly high throughput- biology on steroids- manner. With this coverage, the book will be useful to a diverse array of life science professionals, computational biologists, bioinformaticists, as well as students |
| Bibliography |
Includes bibliographical references and indexes |
| Notes |
Title from title page [viewed February 9, 2014] |
| Subject |
Bioinformatics.
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Computational biology.
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Computational biology.
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Bioinformatics.
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| Form |
Electronic book
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