High-performance algorithms for mass spectrometry-based omics / Fahad Saeed, Muhammad Haseeb.
2022
QD96.M3
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Title
High-performance algorithms for mass spectrometry-based omics / Fahad Saeed, Muhammad Haseeb.
Author
Saeed, Fahad, author.
ISBN
9783031019609 (electronic bk.)
3031019601 (electronic bk.)
9783031019593
3031019598
3031019601 (electronic bk.)
9783031019593
3031019598
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (xvi, 140 pages) : illustrations (chiefly color).
Item Number
10.1007/978-3-031-01960-9 doi
Call Number
QD96.M3
Dewey Decimal Classification
543/.650285
Summary
To date, processing of high-throughput Mass Spectrometry (MS) data is accomplished using serial algorithms. Developing new methods to process MS data is an active area of research but there is no single strategy that focuses on scalability of MS based methods. Mass spectrometry is a diverse and versatile technology for high-throughput functional characterization of proteins, small molecules and metabolites in complex biological mixtures. In the recent years the technology has rapidly evolved and is now capable of generating increasingly large (multiple tera-bytes per experiment) and complex (multiple species/microbiome/high-dimensional) data sets. This rapid advance in MS instrumentation must be matched by equally fast and rapid evolution of scalable methods developed for analysis of these complex data sets. Ideally, the new methods should leverage the rich heterogeneous computational resources available in a ubiquitous fashion in the form of multicore, manycore, CPU-GPU, CPU-FPGA, and IntelPhi architectures. The absence of these high-performance computing algorithms now hinders scientific advancements for mass spectrometry research. In this book we illustrate the need for high-performance computing algorithms for MS based proteomics, and proteogenomics and showcase our progress in developing these high-performance algorithms.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 15, 2022).
Added Author
Haseeb, Muhammad, author.
Series
Computational biology. 2662-2432
Available in Other Form
High-Performance Algorithms for Mass Spectrometry-Based Omics
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Table of Contents
1. Need for High Performance Computing for Big MS Data
2. Introduction to Mass Spectrometry Data
3. A Review of Spectral Pre-processing
4. MS-REDUCE: An Ultra Data Reduction Algorithm
5. GPU-DAEMON: A Template to Support Development of GPU Algorithms
6. GPU-ArraySort: GPU Based Array Sorting Technique
7. G-MSR: A GPU Based Dimensionality Reduction Algorithm
8. Simulator Driven Proteomics
9. Future and Proposed Work.
2. Introduction to Mass Spectrometry Data
3. A Review of Spectral Pre-processing
4. MS-REDUCE: An Ultra Data Reduction Algorithm
5. GPU-DAEMON: A Template to Support Development of GPU Algorithms
6. GPU-ArraySort: GPU Based Array Sorting Technique
7. G-MSR: A GPU Based Dimensionality Reduction Algorithm
8. Simulator Driven Proteomics
9. Future and Proposed Work.