Online Biology Book (M. Farabee)

EBook Description: Online Biology Book (M. Farabee)

Computational Biology Lecture Notes (R.F. Murphy)

Population Genetics (M. Whitlock)

Population Genetics (M. Whitlock)

Relational Modeling of Biological Data Trees and Graphs (A.J. Mackey)

Relational Modeling of Biological Data Trees and Graphs (A.J. Mackey)

Mathematics and Biology The Interface, Challenges, and Opportunities

Mathematics and Biology The Interface, Challenges, and Opportunities

Bioinformatics

This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and computer science background.

Structural Bioinformatics of Membrane Proteins

This book is the first one specifically dedicated to the structural bioinformatics of membrane proteins. With a focus on membrane proteins from the perspective of bioinformatics, the present work covers a broad spectrum of topics in evolution, structure, function, and bioinformatics of membrane proteins focusing on the most recent experimental results. Leaders in the field who have recently reported breakthrough advances cover algorithms, databases and their applications to the subject.

The increasing number of recently solved membrane protein structures makes the expert coverage presented here very timely.

Structural bioinformatics of membrane proteins has been an active area of research over the last thee decades and proves to be a growing field of interest.

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.

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!

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.

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.

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