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Titlebook: High-Performance Algorithms for Mass Spectrometry-Based Omics; Fahad Saeed,Muhammad Haseeb Book 2022 The Editor(s) (if applicable) and The

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發(fā)表于 2025-3-27 00:30:21 | 只看該作者
32#
發(fā)表于 2025-3-27 03:21:45 | 只看該作者
33#
發(fā)表于 2025-3-27 07:21:26 | 只看該作者
34#
發(fā)表于 2025-3-27 09:37:56 | 只看該作者
35#
發(fā)表于 2025-3-27 14:21:18 | 只看該作者
Fast Spectral Pre-processing for Big MS Data,In this chapter, we discuss and introduce a data pre-processing algorithm for dimensionality reduction of big MS data. We will start by discussing a few spectral pre-processing methods followed by the introduction MS-REDUCE which is a highly efficient method for processing MS data.
36#
發(fā)表于 2025-3-27 18:08:51 | 只看該作者
37#
發(fā)表于 2025-3-28 01:49:59 | 只看該作者
Machine-Learning and the Future of HPC for MS-Based Omics,To date, MS proteomics data is identified using database search algorithms based purely on numerical techniques or some denovo techniques that allow peptide identification without using databases. Currently, there is no single strategy from database search or denovo techniques that can claim as the most accurate strategy.
38#
發(fā)表于 2025-3-28 03:45:53 | 只看該作者
https://doi.org/10.1007/978-3-031-01960-9High Performance Computing; Mass Spectrometry; Big Data; Proteomics; Protogenomics
39#
發(fā)表于 2025-3-28 08:04:08 | 只看該作者
Fahad Saeed,Muhammad HaseebNumerous, advanced high-performance computing techniques and algorithms useful for omics practitioners.Suitable for both learning at undergraduate and graduate level as well as professional level.Ther
40#
發(fā)表于 2025-3-28 14:27:06 | 只看該作者
Computational Biologyhttp://image.papertrans.cn/h/image/426640.jpg
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