000			02708cam a2200265 i 4500
020			_a9783031019609
020			_a3031019601
082	0	4	_aQL368 .S24 2022 _b1
100	1		_aSaeed, Fahad,
245	1	0	_aHigh-performance algorithms for mass spectrometry-based omics / _cFahad Saeed, Muhammad Haseeb
264		1	_aCham : _bSpringer, _c[2022]
264		4	_c©2022
300			_a1 online resource (xvi, 140 pages) : _billustrations (chiefly color)
490	1		_aComputational biology,
505	0		_a1. 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
520			_aTo 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
650		0	_aMass spectrometry
650		0	_aHigh performance computing.
650		0	_aComputer algorithms.
700	1		_aHaseeb, Muhammad,
856	4	0	_uhttps://rave.ohiolink.edu/ebooks/ebc2/9783031019609
856	4	0	_uhttps://link.springer.com/10.1007/978-3-031-01960-9
856	4	0	_uhttps://go.ohiolink.edu/goto?url=https://link.springer.com/10.1007/978-3-031-01960-9
942			_2lcc _cBK
999			_c14174 _d14174