Download BookBioinformatics High Performance Parallel Computer Architectures (Embedded Multi-Core Systems)

Download Bioinformatics High Performance Parallel Computer Architectures (Embedded Multi-Core Systems)

Download Bioinformatics High Performance Parallel Computer Architectures (Embedded Multi-Core Systems)

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Book Details :
Published on: 2010-07-15
Released on:
Original language: English

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. Theoretical computer science - Wikipedia Theoretical computer science or TCS is a division or subset of general computer science and mathematics that focuses on more abstract or mathematical aspects of ... Jeremy Kepner - Massachusetts Institute of Technology Electrical Engineering/Computer Science Math/Physics/Astronomy; Julia Implementation of the Dynamic Distributed Dimensional Data Model [Best Paper Award] Alexander ... Department of Electrical Engineering & Computer Science Department of Electrical Engineering & Computer Science 1520 West 15th Street 2001 Eaton Hall University of Kansas Lawrence KS 66045-7608 (785) 864-4620 Computer Science (COMP) Calendars Carleton University School of Computer Science Faculty of Science. Notes: Some of the following Computer Science courses are cross-listed from other parts of the Calendar. Computer Science Stanford University Bachelor of Science in Computer Science. The department offers both a major in Computer Science and a minor in Computer Science. Further information is available in ... Data-intensive applications challenges techniques and ... 1. Introduction. Big Data has been one of the current and future research frontiers. In this year Gartner listed the Top 10 Strategic Technology Trends For 2013 ... Accepted Papers ICML New York City We show how deep learning methods can be applied in the context of crowdsourcing and unsupervised ensemble learning. First we prove that the popular model of Dawid ... NSERC List of Evaluation Groups and Research Topics 1502 Biological Systems and Functions; LSB01: Plant Biology: Plant pathology; water and minerals in plants; plant morphology; plant nutrition and metabolism ... Computer Science and Engineering (CSE) Courses Computer Science and Engineering (CSE) [ MAS-AESE courses undergraduate program graduate program faculty] All courses faculty listings and curricular and ... pdp2014.org Special Session Multi-Core and Many-Core systems for Embedded Computing
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