Presents up-to-date computer methods for analysing DNA, RNA and protein sequences.
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'This book fills an important gap in the bioinformatics literature and should be required reading for anyone who is interested in doing serious work in biological sequence analysis. For biologists who have little formal training in statistics or probability, it is a long-awaited contribution that, short of consulting a professional statistician who is well versed in molecular biology, is the best source of statistical information that is relevant to sequence-alignment problems. This book seems destined to become a classic. I highly recommend it.' Andrew F. Neuwald, Trends in Biochemical Sciences
'This book is a nice tutorial and introduction to the field and can certainly be recommended to all who wish to analyse biological sequences with computer methods. It can also serve as a basis for a university course for undergraduates.' Trends in Cell Biology
' ... an enjoyable opportunity to see a blend of modeling and data analysis at work on an important class of problems in the rapidly growing field of computational biology.' D. Siegmund, Short Book Reviews
Probabilistic methods are assuming greater significance in the analysis of nucleotide sequence data. This book provides the first unified, up-to-date and self-contained account of such methods, and more generally of probabilistic methods of sequence analysis, presented in a Bayesian framework.
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Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Paperback. Condizione: Very Good. 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. Codice articolo CIN0521629713VG
Quantità: 1 disponibili
Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Paperback. Condizione: Good. 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. Codice articolo 00104407928
Quantità: 5 disponibili
Da: Dream Books Co., Denver, CO, U.S.A.
Condizione: acceptable. This copy has clearly been enjoyedâ"expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps. Codice articolo DBV.0521629713.A
Quantità: 1 disponibili
Da: ThriftBooks-Phoenix, Phoenix, AZ, U.S.A.
Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Codice articolo G0521629713I3N00
Quantità: 1 disponibili
Da: ThriftBooks-Reno, Reno, NV, U.S.A.
Paperback. Condizione: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less. Codice articolo G0521629713I5N00
Quantità: 1 disponibili
Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Paperback. Condizione: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less. Codice articolo G0521629713I5N00
Quantità: 1 disponibili
Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Paperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Codice articolo G0521629713I3N00
Quantità: 1 disponibili
Da: World of Books Inc, Montgomery, IL, U.S.A.
Paperback. Condizione: Good. 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. Codice articolo CIN0521629713G
Quantità: 5 disponibili
Da: World of Books Inc, Montgomery, IL, U.S.A.
Paperback. Condizione: Very Good. 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. Codice articolo CIN0521629713VG
Quantità: 1 disponibili
Da: Campus Bookstore, Denton, TX, U.S.A.
Paperback. Condizione: Good. May contain highlighting/underlining/notes/etc. May have used stickers on cover. Access codes and supplements are not guaranteed to be included with used books. Ships same or next day. Expedited shipping: 3-5 business days, Standard shipping: 4-14 business days. Codice articolo mon0000181557
Quantità: 1 disponibili