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Target‐Decoy database is currently the method of choice to assess the quality of Proteins' search engines. Decoy versions of real peptides are generated and injected to the same database of real ones with different labels. Quality of search engines results is assessed based on the number of decoys retrieved as hits. In Crux‐Tide search engine, which is one of the fastest search engines currently available,...
Despite the linear relation between the number of observed spectra and the searching time, the current protein search engines, even the parallel versions, could take several hours to search a large amount of MS/MS spectra, which can be generated in a short time. After a laborious searching process, some (and at times, majority) of the observed spectra are labeled as non-identifiable. We evaluate the...
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...
Deep learning has been successfully applied in several fields such as machine translation, manufacturing, and pattern recognition. However, successful application of deep learning depends upon appropriately setting its parameters to achieve high-quality results. The number of hidden layers and the number of neurons in each layer of a deep machine learning network are two key parameters, which have...
Target-Decoy database is a common dependable strategy used in Peptide-Spectrum-Matching (PSM) for quality assessment. In this, a set of decoy labeled peptides are injected to the database and indexed along with real peptides. Crux Tide is a fast search engine that supports indexing peptides' database and decoys generation. In Tide, indexing FASTA files and generating decoys is a computationally expensive...
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