Sequence Analysis In A Nutshell

This work pulls together all of the vital information about the most commonly used databases, analytical tools, and tables used in sequence analysis.

Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases pulls together all of the vital information about the most commonly used databases, analytical tools, and tables used in sequence analysis.The book is partitioned into three fundamental areas to help you maximize your use of the content. The first section, Databases contains examples of flatfiles from key databases (GenBank, EMBL, SWISS-PROT), the definitions of the codes or fields used in each database, and the sequence feature types/terms and qualifiers for the nucleotide and protein databases.The second section, Tools provides the command line syntax for popular applications such as ReadSeq, MEME/MAST, BLAST, ClustalW, and the EMBOSS suite of analytical tools. The third section, Appendixes concentrates on information essential to understanding the individual components that make up a biological sequence. The tables in this section include nucleotide and protein codes, genetic codes, as well as other relevant information.Written in O'Reilly's enormously popular, straightforward Nutshell format, this book draws together essential information for bioinformaticians in industry and academia, as well as for students.If sequence analysis is part of your daily life, you'll want this easy-to-use book on your desk.

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.

This book gives a general view of sequence analysis, the statistical study of successions of states or events. It includes innovative contributions on life course studies, transitions into and out of employment, contemporaneous and historical careers, and political trajectories. The approach presented in this book is now central to the life-course perspective and the study of social processes more generally. This volume promotes the dialogue between approaches to sequence analysis that developed separately, within traditions contrasted in space and disciplines. It includes the latest developments in sequential concepts, coding, atypical datasets and time patterns, optimal matching and alternative algorithms, survey optimization, and visualization. Field studies include original sequential material related to parenting in 19th-century Belgium, higher education and work in Finland and Italy, family formation before and after German reunification, French Jews persecuted in occupied France, long-term trends in electoral participation, and regime democratization. Overall the book reassesses the classical uses of sequences and it promotes new ways of collecting, formatting, representing and processing them. The introduction provides basic sequential concepts and tools, as well as a history of the method. Chapters are presented in a way that is both accessible to the beginner and informative to the expert.

DNA sequencing has become increasingly efficient over the years, resulting in an enormous increase in the amount of data gen- ated. In recent years, the focus of sequencing has shifted, from being the endpoint of a project, to being a starting point. This is especially true for such major initiatives as the human genome project, where vast tracts of DNA of unknown function are sequenced. This sheer volume of available data makes advanced computer methods ess- tial to analysis, and a familiarity with computers and sequence ana- sis software a vital requirement for the researcher involved with DNA sequencing. Even for nonsequencers, a familiarity with sequence analysis software can be important. For instance, gene sequences already present in the databases can be extremely useful in the design of cloning and genetic manipulation experiments. This two-part work on Analysis of Data is designed to be a practical aid to the researcher who uses computers for the acquisition, storage, or analysis of nucleic acid (and/or p- tein) sequences. Each chapter is written such that a competent sci- tist with basic computer literacy can carry out the procedure successfully at the first attempt by simply following the detailed pr- tical instructions that have been described by the author. A Notes section, which is included at the end of each chapter, provides advice on overcoming the common problems and pitfalls sometimes enco- tered by users of the sequence analysis software. Software packages for both the mainframe and personal computers are described.

This book explores the remarkable information correspondences and probability structures of proteins. Correspondences are pervasive in biochemistry and bioinformatics: proteins share homologies, folding patterns, and mechanisms. Probability structures are just as paramount: folded state graphics reflect Angstrom-scale maps of electron density. The author explores protein sequences (primary structures), both individually and in sets (systems) with the help of probability and information tools. This perspective will enhance the reader’s knowledge of how an important class of molecules is designed and put to task in natural systems, and how we can approach class members in hands-on ways.

Covers the basic computer analyses used for new DNA sequences and attempts to provide the researcher with the necessary background in order to understand and use efficiently these programs.

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.

A timely book for DNA researchers, Automated DNA Sequencing and Analysis reviews and assesses the state of the art of automated DNA sequence analysis-from the construction of clone libraries to the developmentof laboratory and community databases. It presents the methodologies and strategies of automated DNA sequence analysis in a way that allows them to be compared and contrasted. By taking a broad view of the process of automated sequence analysis, the present volume bridges the gap between the protocols supplied with instrument and reaction kits and the finalized data presented in the research literature. It will be an invaluable aid to both small laboratories that are interested in taking maximum advantageof automated sequence resources and to groups pursuing large-scale cDNA and genomic sequencing projects. The field of automation in DAN sequencing and analysis is rapidly moving, this book fulfils those needs, reviews the history of the art and provides pointers to future development.

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.