Computer Methods for Macromolecular Sequence Analysis: Volume 266
Published on 5. July 1996
Book
Hardback
711 pages
978-0-12-182167-8 (ISBN)
Description
The critically acclaimed laboratory standard for more than forty years, Methods in Enzymology is one of the most highly respected publications in the field of biochemistry. Since 1955, each volume has been eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. More than 260 volumes have been published (all of them still in print) and much of the material is relevant even today--truly an essential publication for researchers in all fields of life sciences.
Reviews / Votes
Praise for the Volume"The individual sections of the book are nicely balanced and provide detailed background information as well as outlines of the application and use of many of the programs... Coverage of protein structural predictions is excellent and the individual algorithms are explained in sufficient detail... Large-scale sequence similarity comparisons, detection of distant homologies, and pattern recognition are covered. This section of the book should be particularly useful to new researchers in this area and serve as a reference to those actively involved in the field... The coverage [of the third section] is outstanding and should serve as a useful reference to individuals interested in multiple alignments and phylogenetic tress. The breadth of topics covered by this volume of Methods in Enzymology is outstanding and the book should become very popular among a variety of biological investigators."
--MARK A. BATZER, Louisiana State University Medical Center
Praise for the Series
"The Methods in Enzymology series represents the gold-standard."
--NEUROSCIENCE
"Incomparably useful."
--ANALYTICAL BIOCHEMISTRY
"It is a true 'methods' series, including almost every detail from basic theory to sources of equipment and reagents, with timely documentation provided on each page."
--BIO/TECHNOLOGY
"The series has been following the growing, changing and creation of new areas of science. It should be on the shelves of all libraries in the world as a whole collection."
--CHEMISTRY IN INDUSTRY
"The appearance of another volume in that excellent series, Methods in Enzymology, is always a cause for appreciation for those who wish to successfully carry out a particular technique or prepare an enzyme or metabolic intermediate without the tiresome prospect of searching through unfamiliar literature and perhaps selecting an unproven method which is not easily reproduced."
--AMERICAN SOCIETY OF MICROBIOLOGY NEWS
"If we had some way to find the work most often consulted in the laboratory, it could well be the multi-volume series Methods in Enzymology...a great work."
--ENZYMOLOGIA
"A series that has established itself as a definitive reference for biochemists."
--JOURNAL OF CHROMATOGRAPHY
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Biochemists, molecular biologists, evolutionary biologists, geneticists, cell biologists, and biotechnologists.
Dimensions
Height: 229 mm
Width: 152 mm
Weight
1110 gr
ISBN-13
978-0-12-182167-8 (9780121821678)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Content
Databases and Resources: B. Shomer, R.A.L. Harper, and G.N. Cameron, Information Services of European Bioinformatics Institute. O. White and A.R. Kerlavage, TDB: New Databases for Biological Discovery. D.G.George, L.T. Hunt, and W.C. Barker, PIR-International Protein Sequence Database. W.C. Barker, F. Pfeiffer, and D.G. George, Superfamily Classification in PIR-International Protein Sequence Database. C.H. Wu, Gene Classification ArtificialNeural System. J.G. Henikoff and S. Henikoff, Blocks Database and Its Applications. R. Staden, Indexing and Using Sequence Databases. T. Etzold, A. Ulyanov, and P. Argos, SRS: Information Retrieval System for Molecular Biology Data Banks. Searching through Databases: T.L. Madden, R.L. Tatusov, and J. Zhang, Applications of Network BLAST Server. G.D. Schuler, J.A. Epstein, H. Ohkawa, and J.A. Kans, Entrez: Molecular Biology Database and Retrieval System. P. Bork and T.J. Gibson, Applying Motif and Profile Searches. L. Patthy, Consensus Approaches in Detection of Distant Homologies. M. Gribskov and S. Veretnik, Identification of Sequence Patterns with Profile Analysis. J.-M. Claverie, Effective Large-Scale Sequence Similarity Searches. W.R. Pearson, Effective Protein Sequence Comparison. E.C. Uberbacher, Y. Xu, and R.J. Mural, Discovering and Understanding Genes in Human DNA Sequence Using GRAIL. G. Pesole, M. Attimonelli, and C. Saccone, Linguistic Analysis of Nucleotide Sequences: Algorithms for Pattern Recognition and Analysis of Codon Strategy. E.V. Koonin, R.L. Tatusov, and K.E. Rudd, Protein Sequence Comparison at Genome Scale. T.-M. Yi and E.S. Lander, IterativeTemplate Refinement: Protein-Fold Prediction Using Iterative Search and Hybrid Sequence/Structure Templates. Multiple Alignment and Phylogenetic Trees: W.R. Taylor, Multiple Protein Sequence Alignment: Algorithms and Gap Insertion. D.-F. Feng and R.F. Doolittle, Progressive Alignment of Amino Acid Sequences and Construction of Phylogenetic Trees from Them. D.G. Higgins, J.D. Thompson, and T.J. Gibson, Using CLUSTAL for Multiple Sequence Alignments. J. Hein and J. Stovlbuk, Combined DNA and Protein Alignment. J. Felsenstein, Inferring Phylogenies from Protein Sequences by Parsimony, Distance, and Likelihood Methods. N. Saitou, Reconstruction of Gene Trees from Sequence Data. W.-H. Li and X. Gu, Estimating Evolutionary Distances between DNA Sequences. S.F. Altschul and W. Gish, Local Alignment Statistics. D. Gusfield and P. Stelling, Parametric and Inverse-Parametric Sequence Alignment with XPARAL. Secondary Structure Considerations: C.D.Livingstone and G.J. Barton, Identification of Functional Residues and Secondary Structure from Protein Multiple Sequence Alignment. A. Lupas, Prediction and Analysis of Coiled-Coil Structures. B. Rost, PHD: Predicting One-Dimensional Protein Structure by Profile-Based Neural Networks. J. Garnier, J.-F. Gibrat, and B. Robson, GOR Method for Predicting Protein Secondary Structure from Amino Acid Sequence. J.C. Wootton and S. Federhen, Analysis of Compositionally Biased Regions in Sequence Databases. Three-Dimensional Considerations: M.S. Johnson, A.C.W. May, M.A. Rodionov, and J.P. Overington, Discrimination of Common Protein Folds: Application of Protein Structure to Sequence/Structure Comparisons. J.U. Bowie, K.Zhang, M. Wilmanns, and D. Eisenberg, Three-Dimensional Profiles for Measuring Compatability of Amino Acid Sequence with Three-Dimensional Structure. C.A. Orengo and W.R. Taylor, SSAP: Sequential Structure Alignment Program for Protein StructureComparison. S.E. Brenner, C. Chothia, T.J.P. Hubbard, and A.G. Murzin, Understanding Protein Structure: Using Scop for Fold Interpretation. M.B. Swindells, Detecting Structural Similarities: A User's Guide. L. Holm and C. Sander, Alignment of Three-Dimensional Protein Structures: Network Server for Database Searching. O. Poch and M. Delarue, Converting Sequence Block Alignments into Structural Insights. Author Index. Subject Index.