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Author: Michael Ray Gribskov
Publisher: Oxford University Press, USA
ISBN: 0195098749
Category : Amino acid sequence
Languages : en
Pages : 296
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Book Description
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.
Author: Michael Ray Gribskov
Publisher: Oxford University Press, USA
ISBN: 0195098749
Category : Amino acid sequence
Languages : en
Pages : 296
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Book Description
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.
Author: Russell F. Doolittle
Publisher: University Science Books
ISBN: 9780935702545
Category : Science
Languages : en
Pages : 118
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Book Description
In these days of facile cloning and rapid DNA sequencing, it is not uncommon for investigators to find themselves with a DNA sequence that may or may not code for a known gene product. The sequence is 'open' when read in an appropriate frame, which is to say that there is a long run of amino acid codons before the appearance of a terminator codon. How can we find out if this 'unidentified reading frame' (URF) really codes for a genuine protein, and how can we identify it if it exists? There are two general strategies, both of which can also be applied to the characterization of any 'open reading frame' (ORF), whether or not it has been 'identified'. The first and simplest approach involves computer searching and analysis; the second employs antibodies raised against synthetic peptides patterned on the sequence of the expected gene product. Both methods have been used with great success by many investigators. Each has, nonetheless, its pitfalls and frustrations. This primer is meant to guide the researcher past those obstacles as much as possible. Graduate students and researchers interested in amino acid sequencing; molecular biologists, biochemists, chemists, and biotechnologists.
Author: Richard Durbin
Publisher: Cambridge University Press
ISBN: 113945739X
Category : Science
Languages : en
Pages : 372
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Book Description
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.
Author: Cedric Gondro
Publisher: Springer
ISBN: 3319144758
Category : Medical
Languages : en
Pages : 283
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Book Description
Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for graduate and undergraduate courses in bioinformatics and genomic analysis or for use in lab sessions. How to handle and manage high-throughput genomic data, create automated workflows and speed up analyses in R is also taught. A wide range of R packages useful for working with genomic data are illustrated with practical examples. The key topics covered are association studies, genomic prediction, estimation of population genetic parameters and diversity, gene expression analysis, functional annotation of results using publically available databases and how to work efficiently in R with large genomic datasets. Important principles are demonstrated and illustrated through engaging examples which invite the reader to work with the provided datasets. Some methods that are discussed in this volume include: signatures of selection, population parameters (LD, FST, FIS, etc); use of a genomic relationship matrix for population diversity studies; use of SNP data for parentage testing; snpBLUP and gBLUP for genomic prediction. Step-by-step, all the R code required for a genome-wide association study is shown: starting from raw SNP data, how to build databases to handle and manage the data, quality control and filtering measures, association testing and evaluation of results, through to identification and functional annotation of candidate genes. Similarly, gene expression analyses are shown using microarray and RNAseq data. At a time when genomic data is decidedly big, the skills from this book are critical. In recent years R has become the de facto tool for analysis of gene expression data, in addition to its prominent role in analysis of genomic data. Benefits to using R include the integrated development environment for analysis, flexibility and control of the analytic workflow. Included topics are core components of advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics. This book is also designed to be used by students in computer science and statistics who want to learn the practical aspects of genomic analysis without delving into algorithmic details. The datasets used throughout the book may be downloaded from the publisher’s website.
Author: Mark D. Adams
Publisher: Elsevier
ISBN: 9780127170107
Category : Science
Languages : en
Pages : 400
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Book Description
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.
Author: Eugene V. Koonin
Publisher: Springer Science & Business Media
ISBN: 1475737831
Category : Science
Languages : en
Pages : 482
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Book Description
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.
Author: Ognyan Ivanov
Publisher: IntechOpen
ISBN: 9789533072364
Category : Technology & Engineering
Languages : en
Pages : 726
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Book Description
The rich palette of topics set out in this book provides a sufficiently broad overview of the developments in the field of quality control. By providing detailed information on various aspects of quality control, this book can serve as a basis for starting interdisciplinary cooperation, which has increasingly become an integral part of scientific and applied research.
Author: Henry T. Nguyen
Publisher: Springer
ISBN: 3319641980
Category : Science
Languages : en
Pages : 216
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Book Description
This book examines the application of soybean genome sequences to comparative, structural, and functional genomics. Since the availability of the soybean genome sequence has revolutionized molecular research on this important crop species, the book also describes how the genome sequence has shaped research on transposon biology and applications for gene identification, tilling and positional gene cloning. Further, the book shows how the genome sequence influences research in the areas of genetic mapping, marker development, and genome-wide association mapping for identifying important trait genes and soybean breeding. In closing, the economic and botanical aspects of the soybean are also addressed.
Author: Shawn T. O'Neil
Publisher:
ISBN: 9780870719264
Category : Science
Languages : en
Pages : 0
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Book Description
A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the "natural environment" of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful "pipe" operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.
Author: John S. Kaptein
Publisher:
ISBN:
Category :
Languages : en
Pages : 358
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Book Description
