Essential Bioinformatics: Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

Date Added: 3/7/2011 12:14:21 AM | Visits: 33788

Systems Bioinformatics - An Engineering: This trail-blazing work introduces a quantitative systems approach to bioinformatics research using powerful computational tools drawn from signal processing, circuit analysis, control systems, and communications. It presents the functionality of biological processes in an engineering context to facilitate the application of technical skills in solving the field's challenges, from the lab bench to data analysis and modeling, and to enable reverse engineering from biology in the development of synthetic biological devices.

This first-of-its-kind text explores how the knowledge bases of various technical disciplines relate to, and are observed, in biological systems. You learn fundamental signal processing techniques that are essential to biological data analysis, including biomedical imaging and image processing, feature extraction, classification, and estimation. You gain a thorough understanding of cellular regulatory systems and their similarities to traditional control systems, protein and gene networks, inference networks, and network dynamics. The book also addresses how biology-inspired molecular structures are being used to solve engineering challenges, and how one can mimic biology's designs in creating more robust technologies. Moreover, you discover the latest developments in proteomics, where these tools can make an immense impact due to the number, complexity, and interaction networks of proteins. A major addition under the evolving umbrella of systems biology and bioinformatics, this groundbreaking work points you to new frontiers in the convergence of engineering and biological research.

Date Added: 3/7/2011 12:13:45 AM | Visits: 32914

Statistical Bioinformatics: For Biomedical and Life Science Researchers: This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into topics such as clustering, classification, multi-dimensional visualization, experimental design, statistical resampling, and statistical network analysis.

�Clearly explains the use of bioinformatics tools in life sciences research without requiring an advanced background in math/statistics
�Enables biomedical and life sciences researchers to successfully evaluate the validity of their results and make inferences
�Enables statistical and quantitative researchers to rapidly learn novel statistical concepts and techniques appropriate for large biological data analysis
�Carefully revisits frequently used statistical approaches and highlights their limitations in large biological data analysis
�Offers programming examples and datasets
�Includes chapter problem sets, a glossary, a list of statistical notations, and appendices with references to background mathematical and technical material
�Features supplementary materials, including datasets, links, and a statistical package available online
Statistical Bioinformatics is an ideal textbook for students in medicine, life sciences, and bioengineering, aimed at researchers who utilize computational tools for the analysis of genomic, proteomic, and many other emerging high-throughput molecular data. It may also serve as a rapid introduction to the bioinformatics science for statistical and computational students and audiences who have not experienced such analysis tasks before.

Date Added: 3/7/2011 12:13:20 AM | Visits: 32101

Python for Bioinformatics: Programming knowledge is often necessary for finding a solution to a biological problem. Based on the author�s experience working for an agricultural biotechnology company, Python for Bioinformatics helps scientists solve their biological problems by helping them understand the basics of programming. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language.
The book begins with a very basic introduction that teaches the principles of programming. It then introduces the Biopython package, which can be useful in solving life science problems. The next section covers sophisticated tools for bioinformatics, including relational database management systems and XML. The last part illustrates applications with source code, such as sequence manipulation, filtering vector contamination, calculating DNA melting temperature, parsing a genbank file, inferring splicing sites, and more. The appendices provide a wealth of supplementary information, including instructions for installing Python and Biopython and a Python language and style guide.
By incorporating examples in biology as well as code fragments throughout, the author places a special emphasis on practice, encouraging readers to experiment with the code. He shows how to use Python and the Biopython package for building web applications, genomic annotation, data manipulation, and countless other applications.

Date Added: 3/7/2011 12:12:56 AM | Visits: 34052

Statistical Methods In Bioinformatics An Introduction 2 Ed: Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community." "The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics."--BOOK JACKET.

Date Added: 3/7/2011 12:12:31 AM | Visits: 33193

Bioinformatics and Functional Genomics: "&highly recommended for academic and medical libraries, and for researchers as an introduction and reference&" -- E-Streams, Vol. 7, No. 4

"&this appears to be an excellent textbook for graduate students and upper level undergraduate students." -- Annals of Biomedical Engineering, July 2004 32,7
Review
"I was particularly impressed by the comprehensible and comprehensive treatment of BLAST - the best that I have seen. One is guided from choosing the appropriate type of BLAST program, database and search parameters through to refining and analysing the significance of the search results--all illustrated with clear examples."
--David P. Leader, University of Glasgow

"I would not hesitate for a moment to propose Jonathan Pevsner�s new book as a standard course for biologists who need a serious, practical knowledge of modern bioinformatics. Dr. Pevsner does a masterful job at presenting virtually every major topic in bioinformatics and computational genomics, from the basics of sequence analysis, to microarray data classification, accurately and at a considerable level of detail but without any complex mathematics. In addition to being an extremely useful textbook, Pevsner�s book is a very nice read, due in large part, to carefully constructed questions and suggestions for discussion, and wonderful historical vignettes. In short, a great bioinformatics book for biologists!"
--Eugene V. Koonin, Ph.D., National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland

Date Added: 3/7/2011 12:12:04 AM | Visits: 33456

Bioinformatics: High Performance Parallel Computer Architectures: New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive biological understanding.

A complilation of recent approaches from prominent researchers, Bioinformatics: High Performance Parallel Computer Architectures discusses how to take advantage of bioinformatics applications and algorithms on a variety of modern parallel architectures. Two factors continue to drive the increasing use of modern parallel computer architectures to address problems in computational biology and bioinformatics: high-throughput techniques for DNA sequencing and gene expression analysis�which have led to an exponential growth in the amount of digital biological data�and the multi- and many-core revolution within computer architecture.

Presenting key information about how to make optimal use of parallel architectures, this book:

Describes algorithms and tools including pairwise sequence alignment, multiple sequence alignment, BLAST, motif finding, pattern matching, sequence assembly, hidden Markov models, proteomics, and evolutionary tree reconstruction

Addresses GPGPU technology and the associated massively threaded CUDA programming model

Reviews FPGA architecture and programming

Presents several parallel algorithms for computing alignments on the Cell/BE architecture, including linear-space pairwise alignment, syntenic alignment, and spliced alignment

Assesses underlying concepts and advances in orchestrating the phylogenetic likelihood function on parallel computer architectures (ranging from FPGAs upto the IBM BlueGene/L supercomputer)

Covers several effective techniques to fully exploit the computing capability of many-core CUDA-enabled GPUs to accelerate protein sequence database searching, multiple sequence alignment, and motif finding

Explains a parallel CUDA-based method for correcting sequencing base-pair errors in HTSR data

Because the amount of publicly available sequence data is growing faster than single processor core performance speed, modern bioinformatics tools need to take advantage of parallel computer architectures. Now that the era of the many-core processor has begun, it is expected that future mainstream processors will be parallel systems. Beneficial to anyone actively involved in research and applications, this book helps you to get the most out of these tools and create optimal HPC solutions for bioinformatics.

Date Added: 3/7/2011 12:11:30 AM | Visits: 34170

Grid Computing for Bioinformatics and Computational Biology: Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. This book successfully presents Grid algorithms and their real-world applications, provides details on modern and ongoing research, and explores software frameworks that integrate bioinformatics and computational biology.

Date Added: 3/7/2011 12:11:07 AM | Visits: 32401

Bioinformatics for Dummies 2nd Edition: Were you always curious about biology but were afraid to sit through long hours of dense reading? Did you like the subject when you were in high school but had other plans after you graduated? Now you can explore the human genome and analyze DNA without ever leaving your desktop!

Bioinformatics For Dummies is packed with valuable information that introduces you to this exciting new discipline. This easy-to-follow guide leads you step by step through every bioinformatics task that can be done over the Internet. Forget long equations, computer-geek gibberish, and installing bulky programs that slow down your computer. You�ll be amazed at all the things you can accomplish just by logging on and following these trusty directions. You get the tools you need to:

* Analyze all types of sequences
* Use all types of databases
* Work with DNA and protein sequences
* Conduct similarity searches
* Build a multiple sequence alignment
* Edit and publish alignments
* Visualize protein 3-D structures
* Construct phylogenetic trees

This up-to-date second edition includes newly created and popular databases and Internet programs as well as multiple new genomes. It provides tips for using servers and places to seek resources to find out about what�s going on in the bioinformatics world. Bioinformatics For Dummies will show you how to get the most out of your PC and the right Web tools so you�ll be searching databases and analyzing sequences like a pro!

Date Added: 3/7/2011 12:10:32 AM | Visits: 34297

Introduction to Bioinformatics: A Theoretical and Practical Approach: "...contains very valuable information on a wide range of topics related to bioinformatics research." - Heredity
Product Description
Wayne State Univ. School of Medicine, Detroit, MI. Introduces biological, mathematical, statistical, and computer concepts and tools necessary for physical and life scientists to understand and analyze complex biological data. Includes companion CD-ROM with color graphics, lecture material, and software. Hardcover, softcover available. DNLM: Computational Biology--methods.

Date Added: 3/7/2011 12:10:09 AM | Visits: 32906