Bioinformatics: High Performance Parallel Computer Architectures (Hardcover)
暫譯: 生物資訊學:高效能平行計算機架構 (精裝版)
Bertil Schmidt
- 出版商: CRC
- 出版日期: 2010-07-15
- 售價: $5,980
- 貴賓價: 9.5 折 $5,681
- 語言: 英文
- 頁數: 370
- 裝訂: Hardcover
- ISBN: 1439814880
- ISBN-13: 9781439814888
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相關分類:
生物資訊 Bioinformatics
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商品描述
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.
商品描述(中文翻譯)
新一代的測序技術打破了基因組規模測序的許多實驗障礙,導致提取出大量的序列數據。生物數據庫的擴展使得需要新的方法來利用和應用這些驚人的基因組信息,並將其轉化為實質性的生物學理解。
《生物資訊學:高效能平行計算機架構》匯編了來自知名研究者的最新方法,討論如何在各種現代平行架構上利用生物資訊學應用和算法。兩個因素持續推動現代平行計算機架構在計算生物學和生物資訊學問題上的日益使用:DNA測序和基因表達分析的高通量技術——這導致數字生物數據量的指數增長——以及計算機架構中的多核和多核心革命。
本書提供了如何最佳利用平行架構的關鍵信息,包括:
- 描述了包括成對序列比對、多重序列比對、BLAST、基序尋找、模式匹配、序列組裝、隱馬可夫模型、蛋白質組學和進化樹重建等算法和工具。
- 討論了GPGPU技術及其相關的巨量線程CUDA編程模型。
- 回顧了FPGA架構和編程。
- 提出了幾個在Cell/BE架構上計算比對的平行算法,包括線性空間成對比對、同源比對和拼接比對。
- 評估了在平行計算機架構上協調系統發育似然函數的基本概念和進展(範圍從FPGA到IBM BlueGene/L超級計算機)。
- 涵蓋了幾種有效技術,以充分利用多核心CUDA支持的GPU的計算能力,加速蛋白質序列數據庫搜索、多重序列比對和基序尋找。
- 解釋了一種基於平行CUDA的方法,用於修正HTSR數據中的測序碱基對錯誤。
由於公開可用的序列數據增長速度超過單處理器核心性能的提升,現代生物資訊學工具需要利用平行計算機架構。隨著多核心處理器時代的開始,未來主流處理器預計將是平行系統。本書對任何積極參與研究和應用的人都有益,幫助您充分利用這些工具,創建最佳的高效能計算解決方案以應用於生物資訊學。