Sequence Analysis In Molecular Biology

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 Analysis in Molecular Biology ...

Data Analysis in Molecular Biology and Evolution introduces biologists to DAMBE, a proprietary, user-friendly computer program for molecular data analysis. The unique combination of this book and software will allow biologists not only to understand the rationale behind a variety of computational tools in molecular biology and evolution, but also to gain instant access to these tools for use in their laboratories. Data Analysis in Molecular Biology and Evolution serves as an excellent resource for advanced level undergraduates or graduates as well as for professionals working in the field.

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.

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.

An overview of the field of computing with protein and nucleic acid sequences, aimed at investigators determining sequences, those who analyze them to identify unknown proteins and interpret their function, and those interested in the three-dimensional structures of biological molecules.

Computers have become an essential component of modern biology. They help to manage the vast and increasing amount of biological data and continue to play an integral role in the discovery of new biological relationships. This in silico approach to biology has helped to reshape the modern biological sciences. With the biological revolution now among us, it is imperative that each scientist develop and hone today’s bioinformatics skills, if only at a rudimentary level. Bioinformatics Methods and Protocols was conceived as part of the Methods in Molecular Biology series to meet this challenge and to provide the experienced user with useful tips and an up-to-date overview of current developments. It builds upon the foundation that was provided in the two-volume set published in 1994 entitled Computer Analysis of Sequence Data. We divided Bioinformatics Methods and Protocols into five parts, including a thorough survey of the basic sequence analysis software packages that are available at most institutions, as well as the design and implemen- tion of an essential introductory Bioinformatics course. In addition, we included sections describing specialized noncommercial software, databases, and other resources available as part of the World Wide Web and a stimul- ing discussion of some of the computational challenges biologists now face and likely future solutions.

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.

High Performance Computational Methods for Biological Sequence Analysis presents biological sequence analysis using an interdisciplinary approach that integrates biological, mathematical and computational concepts. These concepts are presented so that computer scientists and biomedical scientists can obtain the necessary background for developing better algorithms and applying parallel computational methods. This book will enable both groups to develop the depth of knowledge needed to work in this interdisciplinary field. This work focuses on high performance computational approaches that are used to perform computationally intensive biological sequence analysis tasks: pairwise sequence comparison, multiple sequence alignment, and sequence similarity searching in large databases. These computational methods are becoming increasingly important to the molecular biology community allowing researchers to explore the increasingly large amounts of sequence data generated by the Human Genome Project and other related biological projects. The approaches presented by the authors are state-of-the-art and show how to reduce analysis times significantly, sometimes from days to minutes. High Performance Computational Methods for Biological Sequence Analysis is tremendously important to biomedical science students and researchers who are interested in applying sequence analyses to their studies, and to computational science students and researchers who are interested in applying new computational approaches to biological sequence analyses.

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.