找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪(fǎng)問(wèn)微社區(qū)

打印 上一主題 下一主題

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

[復(fù)制鏈接]
查看: 16900|回復(fù): 47
樓主
發(fā)表于 2025-3-21 19:17:08 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics
編輯Fahad Saeed,Muhammad Haseeb
視頻videohttp://file.papertrans.cn/427/426640/426640.mp4
概述Numerous, 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
叢書(shū)名稱(chēng)Computational Biology
圖書(shū)封面Titlebook: High-Performance Algorithms for Mass Spectrometry-Based Omics;  Fahad Saeed,Muhammad Haseeb Book 2022 The Editor(s) (if applicable) and The
描述.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 n
出版日期Book 2022
關(guān)鍵詞High Performance Computing; Mass Spectrometry; Big Data; Proteomics; Protogenomics
版次1
doihttps://doi.org/10.1007/978-3-031-01960-9
isbn_softcover978-3-031-01962-3
isbn_ebook978-3-031-01960-9Series ISSN 1568-2684 Series E-ISSN 2662-2432
issn_series 1568-2684
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics影響因子(影響力)




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics被引頻次




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics被引頻次學(xué)科排名




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics年度引用




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics年度引用學(xué)科排名




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics讀者反饋




書(shū)目名稱(chēng)High-Performance Algorithms for Mass Spectrometry-Based Omics讀者反饋學(xué)科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶(hù)組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 23:29:15 | 只看該作者
板凳
發(fā)表于 2025-3-22 04:20:51 | 只看該作者
High-Performance Computing Strategy Using Distributed-Memory Supercomputers,ta [.]. In this technique, the experimental spectral data are compared against a protein sequence database through various search algorithms in order to assign the correct peptide sequence to each experimental spectrum [.]. Since the experimental spectra data (histogram-like data) and the peptide se
地板
發(fā)表于 2025-3-22 06:07:08 | 只看該作者
A Easy to Use Generalized Template to Support Development of GPU Algorithms,techniques. These instruments can produce massive amounts of data that needs to be processed in a scalable fashion to ensure that we can make sense of these data sets from various sources [., .]. As expected, Mass Spectrometry (MS) based omics is essential for precision medicine, cancer research, an
5#
發(fā)表于 2025-3-22 09:42:52 | 只看該作者
Computational CPU-GPU Template for Pre-processing of Floating-Point MS Data,o make data pre- and post-processing decisions [.]. Sorting, and searching of data for an array of number is one of the oldest problems in computer science. There has been significant effort in developing algorithms that can sort very large array [.].
6#
發(fā)表于 2025-3-22 15:07:07 | 只看該作者
Re-configurable Hardware for Computational Proteomics,he implementation of application specific integrated chips (ASIC). Even though FPGAs ran at a clock speed much slower than that of an ASIC, they provided an attractive solution to emulate the design logic and verify the functional and timing performance at the early stages of the design process.
7#
發(fā)表于 2025-3-22 18:13:52 | 只看該作者
since 1990. Swarms were found in the northern Aegean Sea, mainly near coastal areas, but at a lower abundance (max 150 ind. m.) than in the Black Sea. It has been hypothesized that . was introduced to the Aegean Sea by Black Sea water, but its presence in Saronikos Gulf and Elefsis Bay, located in t
8#
發(fā)表于 2025-3-23 00:34:05 | 只看該作者
Fahad Saeed,Muhammad Haseeband Caspian Seas by the American Ctenophore, Mnemiopsis leidyi Agassiz: a multidisciplinary perspective and a comparison with other aquatic invasions”, held on 24 - 26 June 2002 in Baku (Azerbaijan). The meeting was ?nanced by the NATO Division for Scienti?c and Environmental Affairs (Brussels); sub
9#
發(fā)表于 2025-3-23 02:29:56 | 只看該作者
10#
發(fā)表于 2025-3-23 08:23:36 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-10 16:55
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
玉田县| 三门峡市| 永济市| 万全县| 志丹县| 呈贡县| 华宁县| 朝阳区| 来安县| 玛纳斯县| 玉环县| 陵川县| 沾化县| 石阡县| 赣榆县| 莒南县| 东丽区| 鹤岗市| 滕州市| 都匀市| 镇坪县| 石渠县| 南丹县| 兴安盟| 曲周县| 东丰县| 那曲县| 镶黄旗| 鄄城县| 青海省| 嘉定区| 荣成市| 康马县| 都安| 星座| 滨海县| 义乌市| 栾川县| 雷州市| 连城县| 漠河县|