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Journal ArticleDOI

pFind-Alioth: A novel unrestricted database search algorithm to improve the interpretation of high-resolution MS/MS data.

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TLDR
A new algorithm called Alioth, to be integrated into the search engine of pFind, for fast and accurate unrestricted database search on high-resolution MS/MS data, and is comparable to or even faster than the restricted search algorithms tested.
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This article is published in Journal of Proteomics.The article was published on 2015-07-01. It has received 64 citations till now. The article focuses on the topics: Search algorithm & Database search engine.

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Citations
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MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics

TL;DR: A fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables a more than 100-fold improvement in speed over most existing proteome database search tools.
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Comprehensive identification of peptides in tandem mass spectra using an efficient open search engine.

TL;DR: This work presents a sequence-tag-based search engine, Open-pFind, to identify peptides in an ultra-large search space that includes coeluting peptides, unexpected modifications and digestions and detects peptides with higher precision and speed than seven other search engines.
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Detection of early pancreatic ductal adenocarcinoma with thrombospondin-2 and CA19-9 blood markers

TL;DR: The authors report that, THBS2, in combination with the marker CA19-9, boosts detection of the early stages of PDAC in high-risk human populations, and improves the ability of CA 19-9 to distinguish PDAC from pancreatitis.
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pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning

TL;DR: The potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines are shown.
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Chemical proteomics reveals new targets of cysteine sulfinic acid reductase.

TL;DR: DiaAlk provides a novel tool to profile S-sulfinylated proteins and study their regulatory mechanisms in cells, thus illuminating dynamic responses to oxidative stress and enabling the identification of new substrates of sulfiredoxin.
References
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Journal ArticleDOI

Probability-based protein identification by searching sequence databases using mass spectrometry data.

TL;DR: A new computer program, Mascot, is presented, which integrates all three types of search for protein identification by searching a sequence database using mass spectrometry data, and the scoring algorithm is probability based.
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Mass spectrometry-based proteomics

TL;DR: The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.
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An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.

TL;DR: The approach described in this manuscript provides a convenient method to interpret tandem mass spectra with known sequences in a protein database.
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Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

TL;DR: A statistical model is presented to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST, demonstrating that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides.
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Large-scale analysis of the yeast proteome by multidimensional protein identification technology.

TL;DR: MudPIT was applied to the proteome of the Saccharomyces cerevisiae strain BJ5460 grown to mid-log phase and yielded the largest proteome analysis to date, identifying 131 proteins with three or more predicted transmembrane domains which allowed us to map the soluble domains of many of the integral membrane proteins.
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