Dna And Protein Sequence Analysis

Sequence data--either lists of nucleotides or of amino acids--are now easily gathered using automated equipment; the real effort is involved in interpreting the data to produce predictions of protein structure or function. With the advent of worldwide computer networks, a plethora of software is now available for sequence analysis. This book describes the techniques for computer analysis of sequence data, with the emphasis on general issues rather than specific algorithms. Unlike many books on these topics, which focus on the "how-to" aspects of software packages, this one places more emphasis on the science behind the packages and on interpretation of the results.

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.

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Sequence Analysis in Molecular Biology: Treasure Trove or Trivial Pursuit presents the methods for sequence analysis of DNA and proteins. This book contains eight chapters that consider the sequence analysis either directly on a microcomputer or using one of the main sequence/programs data banks. This book starts with a description of the main nucleic acid and protein sequence data banks, followed by a short section on the ""housekeeping aids"" that the computer can provide during a sequencing project. Chapters 4 and 5 deal with nucleic acid and protein sequence analysis. Chapter 6 treats algorithms for homology searching and sequence alignments. Chapter 7 presents some selected examples of how computer modeling can help decide whether an observed sequence pattern is significant or not, and how computer simulation is sometimes used to get a feeling for the behavior of intrinsically complex sequence-dependent processes. Chapter 8 contains some comments on the role of theoretical sequence analysis in molecular biology. This book is directed toward molecular biologists.

Methods in Protein Sequence Analysis contains an intensely prac tical account of all the new methodology available to scientists carrying out protein and peptide sequencing studies. Many of the striking advances in fields as diverse as immunology, cell motility, and neurochemistry have in fact been fueled by our ever more powerful ability to determine the sequences and structures of key proteins and peptides. It is our hope that the rich array of tech niques and methods for sequencing proteins discussed in this volume-methods that generate much of the information crucial to progress in modern biology-will now become accessible to all who can benefit from them. The papers of the present volume constitute the Proceedings of the IVth International Conference on Methods in Protein Se quence Analysis, which was held at Brookhaven National Labo ratory, Upton, NY, September 21-25, 1981. It was the most recent in a series of biennial conferences, the previous one having been held in Heidelberg, GFR, in 1979. The series was originated by Richard Laursen, and initially dealt with one aspect of the field, solid-phase sequencing. The scope of the meeting was very broad and among the many aspects of protein sequencing discussed were: instrumentation, strategy, chemicals, mass spectrometry, cleavage of proteins and separation of peptides, and solid, liquid, manual, and even "gas phase" sequencing.

The recent accumulation of information from genomes, including their sequences, has resultednotonlyinnewattemptstoansweroldquestionsandsolvelongstandingissues inbiology,butalsointheformulationofnovelhypothesesthatarisepreciselyfromthis wealth of data. The storage, processing, description, transmission, connection, and analysis of these data has prompted bioinformatics to become one the most relevant applied sciences for this new century, walking hand-in-hand with modern molecular biology and clearly impacting areas like biotechnology and biomedicine. Bioinformatics skills have now become essential for many scientists working with DNA sequences. With this idea in mind, this book aims to provide practical guidance andtroubleshootingadviceforthecomputationalanalysisofDNAsequences,covering a range of issues and methods that unveil the multitude of applications and relevance that Bioinformatics has today. The analysis of protein sequences has been purposely excludedtogainfocus.Individualbookchaptersareorientedtowardthedescriptionof theuseofspecificbioinformaticstools,accompaniedbypracticalexamples,adiscussion on the interpretation of results, and specific comments on strengths and limitations of the methods and tools. In a sense, chapters could be seen as enriched task-oriented manuals that will direct the reader in completing specific bioinformatics analyses. The target audience for this book is biochemists, and molecular and evolutionary biologiststhatwanttolearnhowtoanalyzeDNAsequencesinasimplebutmeaningful fashion. Readers do not need a special background in statistics, mathematics, or computer science, just a basic knowledge of molecular biology and genetics. All the tools described in the book are free and all of them can be downloaded or accessed throughtheweb.Mostchapterscouldbeusedforpracticaladvancedundergraduateor graduate-level courses in bioinformatics and molecular evolution.

"A reference that should be in the personal library of any biologist who uses the Internet for the analysis of DNA and protein sequence data" --Science

Computerized sequence analysis is an integral part of biotechnological research, yet many biologists have received no formal training in this important technology. Sequence Analysis Primer offers the beginner the necessary background to enter this vital field and helps more seasoned researchers to fine-tune their approach. It covers basic data manipulation such as homology searches, stem-loop identification, and protein secondary structure prediction, and is compatible with most sequence analysis programs. A detailed example giving steps for characterizing a new gene sequence provides users with hands-on experience when combined with their current software. The book will be invaluable to researchers and students in molecular biology, genetics, biochemistry, microbiology, and biotechnology.

As more species' genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories.