AP3: An Advanced Proteotypic Peptide Predictor for Targeted Proteomics by Incorporating Peptide Digestibility

2019 ◽  
Vol 91 (13) ◽  
pp. 8705-8711 ◽  
Author(s):  
Zhiqiang Gao ◽  
Cheng Chang ◽  
Jinghan Yang ◽  
Yunping Zhu ◽  
Yan Fu
2018 ◽  
Author(s):  
Zhiqiang Gao ◽  
Cheng Chang ◽  
Yunping Zhu ◽  
Yan Fu

ABSTRACTMotivationThe selection of proteotypic peptides, i.e., detectable unique representatives of proteins of interest, is a key step in targeted shotgun proteomics. To date, much effort has been made to predict proteotypic peptides in the absence of mass spectrometry data. However, the performance of existing tools is still unsatisfactory. One crucial reason is their neglect of the close relationship between protein proteolytic digestion and peptide detection.ResultsWe present an algorithm (named AP3) that firstly considers peptide digestion probability as a feature for proteotypic peptide prediction and demonstrated peptide digestion probability is the most important feature for accurate prediction of proteotypic peptides. AP3 showed higher accuracy than existing tools and accurately predicted the proteotypic peptides for a targeted proteomics assay, showing its great potential for assisting the design of targeted proteomics experiments.Availability and ImplementationFreely available at http://fugroup.amss.ac.cn/software/AP3/[email protected] or [email protected] InformationSupplementary data are available at Bioinformatics online.


2014 ◽  
Vol 14 (3) ◽  
pp. 344-350 ◽  
Author(s):  
Yassel Gomez ◽  
Sebastien Gallien ◽  
Vivian Huerta ◽  
Jan Oostrum ◽  
Bruno Domon ◽  
...  

2014 ◽  
Vol 8 (7-8) ◽  
pp. 543-553 ◽  
Author(s):  
Genaro A. Ramirez-Correa ◽  
Maria Isabel Martinez-Ferrando ◽  
Pingbo Zhang ◽  
Anne M. Murphy

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