Literature DB >> 15817687

pFind: a novel database-searching software system for automated peptide and protein identification via tandem mass spectrometry.

Dequan Li1, Yan Fu, Ruixiang Sun, Charles X Ling, Yonggang Wei, Hu Zhou, Rong Zeng, Qiang Yang, Simin He, Wen Gao.   

Abstract

SUMMARY: Research in proteomics requires powerful database-searching software to automatically identify protein sequences in a complex protein mixture via tandem mass spectrometry. In this paper, we describe a novel database-searching software system called pFind (peptide/protein Finder), which employs an effective peptide-scoring algorithm that we reported earlier. The pFind server is implemented with the C++ STL, .Net and XML technologies. As a result, high speed and good usability of the software are achieved.

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Year:  2005        PMID： 15817687     DOI： 10.1093/bioinformatics/bti439

Source DB:  PubMed          Journal:  Bioinformatics        ISSN： 1367-4803            Impact factor:   6.937


  47 in total

1.  Monitoring Cellular Phosphorylation Signaling Pathways into Chromatin and Down to the Gene Level.

Authors:  Yumiao Han; Zuo-Fei Yuan; Rosalynn C Molden; Benjamin A Garcia
Journal:  Mol Cell Proteomics       Date:  2015-11-05       Impact factor: 5.911

2.  Quantitative Profiling of the Activity of Protein Lysine Methyltransferase SMYD2 Using SILAC-Based Proteomics.

Authors:  Jonathan B Olsen; Xing-Jun Cao; Bomie Han; Lisa Hong Chen; Alexander Horvath; Timothy I Richardson; Robert M Campbell; Benjamin A Garcia; Hannah Nguyen
Journal:  Mol Cell Proteomics       Date:  2016-01-10       Impact factor: 5.911

3.  A strategy for precise and large scale identification of core fucosylated glycoproteins.

Authors:  Wei Jia; Zhuang Lu; Yan Fu; Hai-Peng Wang; Le-Heng Wang; Hao Chi; Zuo-Fei Yuan; Zhao-Bin Zheng; Li-Na Song; Huan-Huan Han; Yi-Min Liang; Jing-Lan Wang; Yun Cai; Yu-Kui Zhang; Yu-Lin Deng; Wan-Tao Ying; Si-Min He; Xiao-Hong Qian
Journal:  Mol Cell Proteomics       Date:  2009-01-12       Impact factor: 5.911

4.  Transferred subgroup false discovery rate for rare post-translational modifications detected by mass spectrometry.

Authors:  Yan Fu; Xiaohong Qian
Journal:  Mol Cell Proteomics       Date:  2013-11-07       Impact factor: 5.911

5.  Various conotoxin diversifications revealed by a venomic study of Conus flavidus.

Authors:  Aiping Lu; Longjin Yang; Shaoqiong Xu; Chunguang Wang
Journal:  Mol Cell Proteomics       Date:  2013-10-14       Impact factor: 5.911

6.  From raw data to biological discoveries: a computational analysis pipeline for mass spectrometry-based proteomics.

Authors:  Mathieu Lavallée-Adam; Sung Kyu Robin Park; Salvador Martínez-Bartolomé; Lin He; John R Yates
Journal:  J Am Soc Mass Spectrom       Date:  2015-05-22       Impact factor: 3.109

7.  UvrD facilitates DNA repair by pulling RNA polymerase backwards.

Authors:  Vitaly Epshtein; Venu Kamarthapu; Katelyn McGary; Vladimir Svetlov; Beatrix Ueberheide; Sergey Proshkin; Alexander Mironov; Evgeny Nudler
Journal:  Nature       Date:  2014-01-08       Impact factor: 49.962

8.  Evaluating protein interactions through cross-linking mass spectrometry.

Authors:  David L Tabb
Journal:  Nat Methods       Date:  2012-09       Impact factor: 28.547

9.  Open MS/MS spectral library search to identify unanticipated post-translational modifications and increase spectral identification rate.

Authors:  Ding Ye; Yan Fu; Rui-Xiang Sun; Hai-Peng Wang; Zuo-Fei Yuan; Hao Chi; Si-Min He
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

10.  An Efficient Dynamic Programming Algorithm for Phosphorylation Site Assignment of Large-Scale Mass Spectrometry Data.

Authors:  Fahad Saeed; Trairak Pisitkun; Jason D Hoffert; Guanghui Wang; Marjan Gucek; Mark A Knepper
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2012-10-04
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