Literature DB >> 15473689

DBParser: web-based software for shotgun proteomic data analyses.

Xiaoyu Yang1, Vijay Dondeti, Rebecca Dezube, Dawn M Maynard, Lewis Y Geer, Jonathan Epstein, Xiongfong Chen, Sanford P Markey, Jeffrey A Kowalak.   

Abstract

We describe a web-based program called 'DBParser' for rapidly culling, merging, and comparing sequence search engine results from multiple LC-MS/MS peptide analyses. DBParser employs the principle of parsimony to consolidate redundant protein assignments and derive the most concise set of proteins consistent with all of the assigned peptide sequences observed in an experiment or series of experiments. The resulting reports summarize peptide and protein identifications from multidimensional experiments that may contain a single data set or combine data from a group of data sets, all related to a single analytical sample. Additionally, the results of multiple experiments, each of which may contain several data sets, can be compared in reports that identify features that are common or different. DBParser actively links to the primary mass spectral data and to public online databases such as NCBI, GO, and Swiss-Prot in order to structure contextually specific reports for biologists and biochemists.

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Year:  2004        PMID: 15473689     DOI: 10.1021/pr049920x

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  34 in total

1.  Generic comparison of protein inference engines.

Authors:  Manfred Claassen; Lukas Reiter; Michael O Hengartner; Joachim M Buhmann; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2011-11-04       Impact factor: 5.911

2.  The α-granule proteome: novel proteins in normal and ghost granules in gray platelet syndrome.

Authors:  D M Maynard; H F G Heijnen; W A Gahl; M Gunay-Aygun
Journal:  J Thromb Haemost       Date:  2010-05-27       Impact factor: 5.824

3.  The effects of chronic treatment with mood stabilizers on the rat hippocampal post-synaptic density proteome.

Authors:  Dhaval Nanavati; Daniel R Austin; Lisa A Catapano; David A Luckenbaugh; Ayse Dosemeci; Husseini K Manji; Guang Chen; Sanford P Markey
Journal:  J Neurochem       Date:  2011-09-21       Impact factor: 5.372

4.  Verification of automated peptide identifications from proteomic tandem mass spectra.

Authors:  David L Tabb; David B Friedman; Amy-Joan L Ham
Journal:  Nat Protoc       Date:  2006       Impact factor: 13.491

5.  Proteomic parsimony through bipartite graph analysis improves accuracy and transparency.

Authors:  Bing Zhang; Matthew C Chambers; David L Tabb
Journal:  J Proteome Res       Date:  2007-08-04       Impact factor: 4.466

6.  Challenges and solutions in proteomics.

Authors:  Huang Hongzhan; Hem D Shukla; Wu Cathy; Saxena Satya
Journal:  Curr Genomics       Date:  2007-03       Impact factor: 2.236

7.  Bayesian nonparametric model for the validation of peptide identification in shotgun proteomics.

Authors:  Jiyang Zhang; Jie Ma; Lei Dou; Songfeng Wu; Xiaohong Qian; Hongwei Xie; Yunping Zhu; Fuchu He
Journal:  Mol Cell Proteomics       Date:  2008-11-12       Impact factor: 5.911

8.  Ultrafast Peptide Label-Free Quantification with FlashLFQ.

Authors:  Robert J Millikin; Stefan K Solntsev; Michael R Shortreed; Lloyd M Smith
Journal:  J Proteome Res       Date:  2017-11-08       Impact factor: 4.466

9.  YPED: a web-accessible database system for protein expression analysis.

Authors:  Mark A Shifman; Yuli Li; Christopher M Colangelo; Kathryn L Stone; Terence L Wu; Kei-Hoi Cheung; Perry L Miller; Kenneth R Williams
Journal:  J Proteome Res       Date:  2007-09-15       Impact factor: 4.466

10.  PGCA: An algorithm to link protein groups created from MS/MS data.

Authors:  David Kepplinger; Mandeep Takhar; Mayu Sasaki; Zsuzsanna Hollander; Derek Smith; Bruce McManus; W Robert McMaster; Raymond T Ng; Gabriela V Cohen Freue
Journal:  PLoS One       Date:  2017-05-31       Impact factor: 3.240

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