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Viser: Biological Sequence Analysis - Probabilistic Models of Proteins and Nucleic Acids
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Biological Sequence Analysis Vital Source e-bog
Richard Durbin, Sean R. Eddy, Anders Krogh og Graeme Mitchison
(1998)
Cambridge University Press
724,00 kr.
Leveres umiddelbart efter køb
Søgbar e-bog
Biological Sequence Analysis Vital Source e-bog
Richard Durbin, Sean R. Eddy, Anders Krogh og Graeme Mitchison
(1998)
Cambridge University Press
724,00 kr.
Leveres umiddelbart efter køb
Biological Sequence Analysis
Probabilistic Models of Proteins and Nucleic Acids
Richard Durbin, Sean R. Eddy, Anders S. Krogh og Graeme Mitchison
(1998)
Sprog: Engelsk
Cambridge University Press
737,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: Cambridge University Press (April 1998)
- Forfattere: Richard Durbin, Sean R. Eddy, Anders Krogh og Graeme Mitchison
- ISBN: 9781107085015
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
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Print: 5 sider kan printes ad gangen
Copy: højest 5 sider i alt kan kopieres (copy/paste)
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 5 sider kan printes ad gangen
Copy: højest 5 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Vital Source searchable e-book (Fixed pages)
- Udgiver: Cambridge University Press (April 1998)
- Forfattere: Richard Durbin, Sean R. Eddy, Anders Krogh og Graeme Mitchison
- ISBN: 9780511252259
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Licens varighed:
Bookshelf online: 5 år 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)
Bookshelf online: 5 år 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: 370 sider
- Udgiver: Cambridge University Press (April 1998)
- Forfattere: Richard Durbin, Sean R. Eddy, Anders S. Krogh og Graeme Mitchison
- ISBN: 9780521629713
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
1. Introduction;
2. Pairwise sequence alignment;
3. Multiple alignments;
4. Hidden Markov models;
5. Hidden Markov models applied to biological sequences;
6. The Chomsky hierarchy of formal grammars;
7. RNA and stochastic context-free grammars;
8. Phylogenetic trees;
9. Phylogeny and alignment; Index.
2. Pairwise sequence alignment;
3. Multiple alignments;
4. Hidden Markov models;
5. Hidden Markov models applied to biological sequences;
6. The Chomsky hierarchy of formal grammars;
7. RNA and stochastic context-free grammars;
8. Phylogenetic trees;
9. Phylogeny and alignment; Index.
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