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OpenMS-Simulator: an open-source software for theoretical tandem mass spectrum prediction

Overview of attention for article published in BMC Bioinformatics, April 2015
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Title
OpenMS-Simulator: an open-source software for theoretical tandem mass spectrum prediction
Published in
BMC Bioinformatics, April 2015
DOI 10.1186/s12859-015-0540-1
Pubmed ID
Authors

Yaojun Wang, Fei Yang, Peng Wu, Dongbo Bu, Shiwei Sun

Abstract

Tandem mass spectrometry (MS/MS) acts as a key technique for peptide identification. The MS/MS-based peptide identification approaches can be categorized into two families, namely, de novo and database search. Both of the two types of approaches can benefit from an accurate prediction of theoretical spectrum. A theoretical spectrum consists of m/z and intensity of possibly occurring ions, which are estimated via simulating the spectrum generating process. Extensive researches have been conducted for theoretical spectrum prediction; however, the prediction methods suffer from low prediciton accuracy due to oversimplifications in the spectrum simulation process. In the study, we present an open-source software package, called OpenMS-Simulator, to predict theoretical spectrum for a given peptide sequence. Based on the mobile-proton hypothesis for peptide fragmentation, OpenMS-Simulator trained a closed-form model for the intensity ratio of adjacent y ions, from which the whole theoretical spectrum can be constructed. On a collection of representative spectra datasets with annotated peptide sequences, experimental results suggest that OpenMS-Simulator can predict theoretical spectra with considerable accuracy. The study also presents an application of OpenMS-Simulator: the similarity between theoretical spectra and query spectra can be used to re-rank the peptide sequence reported by SEQUEST/X!Tandem. OpenMS-Simulator implements a novel model to predict theoretical spectrum for a given peptide sequence. Compared with existing theoretical spectrum prediction tools, say MassAnalyzer and MSSimulator, our method not only simplifies the computation process, but also improves the prediction accuracy. Currently, OpenMS-Simulator supports the prediction of CID and HCD spectrum for peptides with double charges. The extension to cover more fragmentation models and support multiple-charged peptides remains as one of the future works.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Brazil 1 2%
Unknown 54 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 23%
Researcher 13 23%
Student > Master 7 13%
Student > Bachelor 4 7%
Student > Postgraduate 3 5%
Other 7 13%
Unknown 9 16%
Readers by discipline Count As %
Chemistry 13 23%
Computer Science 8 14%
Agricultural and Biological Sciences 8 14%
Biochemistry, Genetics and Molecular Biology 7 13%
Chemical Engineering 2 4%
Other 7 13%
Unknown 11 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 April 2015.
All research outputs
#15,867,545
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#5,494
of 7,418 outputs
Outputs of similar age
#159,276
of 265,233 outputs
Outputs of similar age from BMC Bioinformatics
#111
of 142 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.