Deep Learning-based MSMS Spectra Reduction in Support of Running Multiple Protein Search Engines on Cloud.

ABSTRACT: The diversity of the available protein search engines with respect to the utilized matching algorithms, the low overlap ratios among their results and the disparity of their coverage encourage the community of proteomics to utilize ensemble solutions of different search engines. The advancing in cloud computing technology and the availability of distributed processing clusters can also provide support to this task. However, data transferring and results' combining, in this case, could be the major bottleneck. The flood of billions of observed mass spectra, hundreds of Gigabytes or potentially Terabytes of data, could easily cause the congestions, increase the risk of failure, poor performance, add more computations' cost, and waste available resources. Therefore, in this study, we propose

SUBMITTER: Maabreh M 

PROVIDER: S-EPMC8382039 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature