1.

Record Nr.

UNINA9910809096003321

Titolo

Bioinformatics : high performance parallel computer architectures / / edited by Bertil Schmidt

Pubbl/distr/stampa

Boca Raton, FL, : CRC Press, 2010

ISBN

0-429-13222-0

1-4398-1489-9

Edizione

[1st ed.]

Descrizione fisica

1 online resource (372 p.)

Collana

Embedded multi-core systems

Altri autori (Persone)

SchmidtBertil

Disciplina

572.80285

Soggetti

Bioinformatics - Data processing

Parallel processing (Electronic computers)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Front cover; Contents; Editor; Contributors; Chapter 1: Algorithms for Bioinformatics; Chapter 2: Introduction to GPGPUs andMassively Threaded Programming; Chapter 3: FPGA: Architecture and Programming; Chapter 4: Parallel Algorithms forAlignments on the Cell BE; Chapter 5: Orchestrating the PhylogeneticLikelihood Function on EmergingParallel Architectures; Chapter 6: Parallel Bioinformatics Algorithmsfor CUDA-Enabled GPUs; Chapter 7: CUDA Error Correction Method forHigh-Throughput Short-Read Sequencing Data; Chapter 8: FPGA Acceleration of SeededSimilarity Searching

Chapter 9: Seed-Based Parallel Protein SequenceComparison Combining Multithreading,GPU, and FPGA TechnologiesChapter 10: Database Searching with Profi le-HiddenMarkov Models on Reconfi gurableand Many-Core Architectures; Chapter 11: COPACOBANA: A Massively ParallelFPGA-Based Computer Architecture; Chapter 12: Accelerating String Set Matching forBioinformatics Using FPGA Hardware; Chapter 13: Reconfi gurable Neural System and ItsApplication to Dimeric ProteinBinding Site Identification; Chapter 14: Parallel FPGA Search Enginefor Protein Identification; Index; Back cover

Sommario/riassunto

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 o