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Viser: Understanding Bioinformatics
Understanding Bioinformatics Vital Source e-bog
Marketa J Zvelebil og Jeremy O. Baum
(2007)
Understanding Bioinformatics Vital Source e-bog
Marketa Zvelebil og Jeremy O. Baum
(2007)
Understanding Bioinformatics
Marketa Zvelebil og Jeremy O. Baum
(2007)
Sprog: Engelsk
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Fixed pages): 798 sider
- Udgiver: Garland Science (August 2007)
- Forfattere: Marketa J Zvelebil og Jeremy O. Baum
- ISBN: 9781136976964
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
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Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: Garland Science (August 2007)
- Forfattere: Marketa Zvelebil og Jeremy O. Baum
- ISBN: 9781136976957
Bookshelf online: 365 dage fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: -1 sider kan printes ad gangen
Copy: højest -1 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Paperback: 772 sider
- Udgiver: CRC Press LLC (September 2007)
- Forfattere: Marketa Zvelebil og Jeremy O. Baum
- ISBN: 9780815340249
Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics provides a definitive guide to this vibrant and evolving discipline. The book takes a conceptual approach. It guides the reader from first principles through to an understanding of the computational techniques and the key algorithms. Understanding Bioinformatics is an invaluable companion for students from their first encounter with the subject through to more advanced studies.
The book is divided into seven parts, with the opening part introducing the basics of nucleic acids, proteins and databases. Subsequent parts are divided into 'Applications' and 'Theory' Chapters, allowing readers to focus their attention effectively. In each section, the Applications Chapter provides a fast and straightforward route to understanding the main concepts and 'getting started'. Each of these is then followed by Theory Chapters which give greater detail and present the underlying mathematics. In Part 2, Sequence Alignments, the Applications Chapter shows the reader how to get started on producing and analyzing sequence alignments, and using sequences for database searching, while the next two chapters look closely at the more advanced techniques and the mathematical algorithms involved. Part 3 covers evolutionary processes and shows how bioinformatics can be used to help build phylogenetic trees. Part 4 looks at the characteristics of whole genomes. In Parts 5 and 6 the focus turns to secondary and tertiary structure - predicting structural conformation and analysing structure-function relationships. The last part surveys methods of analyzing data from a set of genes or proteins of an organism and is rounded off with an overview of systems biology.
The writing style of Understanding Bioinformatics is notable for its clarity, while the extensive, full-color artwork has been designed to present the key concepts with simplicity and consistency. Each chapter uses mind-maps and flow diagrams to give an overview of the conceptual links within each topic.
Part 1: Background Basics
1. The Nucleic Acid World
2. Protein Structure
3. Dealing with Databases
Part 2: Sequence Alignments
4. Producing and Analyzing Sequence Alignments
5. Pairwise Sequence Alignment and Database Searching
6. Patterns, Profiles, and Multiple Alignments
Part 3: Evolutionary Processes
7. Recovering Evolutionary History
8. Building Phylogenetic Trees
Part 4: Genome Characteristics
9. Revealing Genome Features
10. Gene Detection and Genome Annotation
Part 5: Secondary Structures
11. Obtaining Secondary Structure from Sequence
12. Predicting Secondary Structures
Part 6: Tertiary Structures
13. Modeling Protein Structure
14. Analyzing Structure-Function Relationships
Part 7: Cells and Organisms
15. Proteome and Gene Expression Analysis
16. Clustering Methods and Statistics
17. Systems Biology Appendices: Background Theory Appendix A. Probability, Information, and Bayesian Analysis Appendix B. Molecular Energy Functions Appendix C. Function Optimization