Literature DB >> 29092938

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

Bobbie-Jo M Webb-Robertson1, Lisa M Bramer2, Jeffrey L Jensen2, Markus A Kobold2, Kelly G Stratton2, Amanda M White2, Karin D Rodland2.   

Abstract

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR. ©2017 American Association for Cancer Research.

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Year:  2017        PMID： 29092938      PMCID： PMC5679244          DOI： 10.1158/0008-5472.CAN-17-0335

Source DB:  PubMed          Journal:  Cancer Res        ISSN： 0008-5472            Impact factor:   12.701


  12 in total

1.  Bayesian proteoform modeling improves protein quantification of global proteomic measurements.

Authors:  Bobbie-Jo M Webb-Robertson; Melissa M Matzke; Susmita Datta; Samuel H Payne; Jiyun Kang; Lisa M Bramer; Carrie D Nicora; Anil K Shukla; Thomas O Metz; Karin D Rodland; Richard D Smith; Mark F Tardiff; Jason E McDermott; Joel G Pounds; Katrina M Waters
Journal:  Mol Cell Proteomics       Date:  2014-12       Impact factor: 5.911

2.  ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC-MS/MS Experiments.

Authors:  Meena Choi; Zeynep F Eren-Dogu; Christopher Colangelo; John Cottrell; Michael R Hoopmann; Eugene A Kapp; Sangtae Kim; Henry Lam; Thomas A Neubert; Magnus Palmblad; Brett S Phinney; Susan T Weintraub; Brendan MacLean; Olga Vitek
Journal:  J Proteome Res       Date:  2017-01-03       Impact factor: 4.466

Review 3.  Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics.

Authors:  Bobbie-Jo M Webb-Robertson; Holli K Wiberg; Melissa M Matzke; Joseph N Brown; Jing Wang; Jason E McDermott; Richard D Smith; Karin D Rodland; Thomas O Metz; Joel G Pounds; Katrina M Waters
Journal:  J Proteome Res       Date:  2015-04-22       Impact factor: 4.466

Review 4.  A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments.

Authors:  Melissa M Matzke; Joseph N Brown; Marina A Gritsenko; Thomas O Metz; Joel G Pounds; Karin D Rodland; Anil K Shukla; Richard D Smith; Katrina M Waters; Jason E McDermott; Bobbie-Jo Webb-Robertson
Journal:  Proteomics       Date:  2012-11-08       Impact factor: 3.984

5.  Phosphotyrosine signaling analysis in human tumors is confounded by systemic ischemia-driven artifacts and intra-specimen heterogeneity.

Authors:  Aaron S Gajadhar; Hannah Johnson; Robbert J C Slebos; Kent Shaddox; Kerry Wiles; Mary Kay Washington; Alan J Herline; Douglas A Levine; Daniel C Liebler; Forest M White
Journal:  Cancer Res       Date:  2015-02-10       Impact factor: 12.701

6.  Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences.

Authors:  Jeremy Goecks; Anton Nekrutenko; James Taylor
Journal:  Genome Biol       Date:  2010-08-25       Impact factor: 13.583

7.  Combined statistical analyses of peptide intensities and peptide occurrences improves identification of significant peptides from MS-based proteomics data.

Authors:  Bobbie-Jo M Webb-Robertson; Lee Ann McCue; Katrina M Waters; Melissa M Matzke; Jon M Jacobs; Thomas O Metz; Susan M Varnum; Joel G Pounds
Journal:  J Proteome Res       Date:  2010-10-08       Impact factor: 4.466

8.  Improved quality control processing of peptide-centric LC-MS proteomics data.

Authors:  Melissa M Matzke; Katrina M Waters; Thomas O Metz; Jon M Jacobs; Amy C Sims; Ralph S Baric; Joel G Pounds; Bobbie-Jo M Webb-Robertson
Journal:  Bioinformatics       Date:  2011-08-18       Impact factor: 6.937

9.  Proteomic analysis of colon and rectal carcinoma using standard and customized databases.

Authors:  Robbert J C Slebos; Xia Wang; Xiaojing Wang; Xaojing Wang; Bing Zhang; David L Tabb; Daniel C Liebler
Journal:  Sci Data       Date:  2015-06-23       Impact factor: 6.444

10.  Proteogenomics connects somatic mutations to signalling in breast cancer.

Authors:  Philipp Mertins; D R Mani; Kelly V Ruggles; Michael A Gillette; Karl R Clauser; Pei Wang; Xianlong Wang; Jana W Qiao; Song Cao; Francesca Petralia; Emily Kawaler; Filip Mundt; Karsten Krug; Zhidong Tu; Jonathan T Lei; Michael L Gatza; Matthew Wilkerson; Charles M Perou; Venkata Yellapantula; Kuan-lin Huang; Chenwei Lin; Michael D McLellan; Ping Yan; Sherri R Davies; R Reid Townsend; Steven J Skates; Jing Wang; Bing Zhang; Christopher R Kinsinger; Mehdi Mesri; Henry Rodriguez; Li Ding; Amanda G Paulovich; David Fenyö; Matthew J Ellis; Steven A Carr
Journal:  Nature       Date:  2016-05-25       Impact factor: 49.962
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  3 in total

1.  P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data.

Authors:  Lisa M Bramer; Kelly G Stratton; Amanda M White; Ameila H Bleeker; Markus A Kobold; Katrina M Waters; Thomas O Metz; Karin D Rodland; Bobbie-Jo M Webb-Robertson
Journal:  J Proteome Res       Date:  2019-02-06       Impact factor: 4.466

2.  Itaconic acid production is regulated by LaeA in Aspergillus pseudoterreus.

Authors:  Kyle R Pomraning; Ziyu Dai; Nathalie Munoz; Young-Mo Kim; Yuqian Gao; Shuang Deng; Teresa Lemmon; Marie S Swita; Jeremy D Zucker; Joonhoon Kim; Stephen J Mondo; Ellen Panisko; Meagan C Burnet; Bobbie-Jo M Webb-Robertson; Beth Hofstad; Scott E Baker; Kristin E Burnum-Johnson; Jon K Magnuson
Journal:  Metab Eng Commun       Date:  2022-08-24

3.  ERBB2 promoter demethylation and immune cell infiltration promote a poor prognosis for cancer patients.

Authors:  Hongting Wang; Yongxu Jiang; Huanhuan Jin; Cunqin Wang
Journal:  Front Oncol       Date:  2022-09-12       Impact factor: 5.738
  3 in total

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