Literature DB >> 26658470

Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0.

Paulo C Carvalho1,2, Diogo B Lima1, Felipe V Leprevost1,3, Marlon D M Santos1, Juliana S G Fischer1, Priscila F Aquino4, James J Moresco5, John R Yates5, Valmir C Barbosa6.   

Abstract

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for the analysis of shotgun proteomic data. The contained modules allow for formatting of sequence databases, peptide spectrum matching, statistical filtering and data organization, extracting quantitative information from label-free and chemically labeled data, and analyzing statistics for differential proteomics. PatternLab also has modules to perform similarity-driven studies with de novo sequencing data, to evaluate time-course experiments and to highlight the biological significance of data with regard to the Gene Ontology database. The PatternLab for proteomics 4.0 package brings together all of these modules in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats. All updates to PatternLab, including new features, have been previously tested on millions of mass spectra. PatternLab is easy to install, and it is freely available from http://patternlabforproteomics.org.

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Year:  2015        PMID: 26658470      PMCID: PMC5722229          DOI: 10.1038/nprot.2015.133

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  64 in total

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Authors:  A Shevchenko; S Sunyaev; A Loboda; A Shevchenko; P Bork; W Ens; K G Standing
Journal:  Anal Chem       Date:  2001-05-01       Impact factor: 6.986

2.  Accurate quantitation of protein expression and site-specific phosphorylation.

Authors:  Y Oda; K Huang; F R Cross; D Cowburn; B T Chait
Journal:  Proc Natl Acad Sci U S A       Date:  1999-06-08       Impact factor: 11.205

3.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

Authors:  Andrew Keller; Alexey I Nesvizhskii; Eugene Kolker; Ruedi Aebersold
Journal:  Anal Chem       Date:  2002-10-15       Impact factor: 6.986

4.  Spectral networks: a new approach to de novo discovery of protein sequences and posttranslational modifications.

Authors:  Nuno Bandeira
Journal:  Biotechniques       Date:  2007-06       Impact factor: 1.993

Review 5.  Venoms, venomics, antivenomics.

Authors:  Juan J Calvete; Libia Sanz; Yamileth Angulo; Bruno Lomonte; José María Gutiérrez
Journal:  FEBS Lett       Date:  2009-03-20       Impact factor: 4.124

6.  Comparative proteomic analysis of the aging soleus and extensor digitorum longus rat muscles using TMT labeling and mass spectrometry.

Authors:  Daniela F S Chaves; Paulo C Carvalho; Diogo B Lima; Humberto Nicastro; Fábio M Lorenzeti; Mário Siqueira-Filho; Sandro M Hirabara; Paulo H M Alves; James J Moresco; John R Yates; Antonio H Lancha
Journal:  J Proteome Res       Date:  2013-09-25       Impact factor: 4.466

7.  SIM-XL: A powerful and user-friendly tool for peptide cross-linking analysis.

Authors:  Diogo B Lima; Tatiani B de Lima; Tiago S Balbuena; Ana Gisele C Neves-Ferreira; Valmir C Barbosa; Fábio C Gozzo; Paulo C Carvalho
Journal:  J Proteomics       Date:  2015-01-29       Impact factor: 4.044

8.  One-hour proteome analysis in yeast.

Authors:  Alicia L Richards; Alexander S Hebert; Arne Ulbrich; Derek J Bailey; Emma E Coughlin; Michael S Westphall; Joshua J Coon
Journal:  Nat Protoc       Date:  2015-04-09       Impact factor: 13.491

9.  A cross-platform toolkit for mass spectrometry and proteomics.

Authors:  Matthew C Chambers; Brendan Maclean; Robert Burke; Dario Amodei; Daniel L Ruderman; Steffen Neumann; Laurent Gatto; Bernd Fischer; Brian Pratt; Jarrett Egertson; Katherine Hoff; Darren Kessner; Natalie Tasman; Nicholas Shulman; Barbara Frewen; Tahmina A Baker; Mi-Youn Brusniak; Christopher Paulse; David Creasy; Lisa Flashner; Kian Kani; Chris Moulding; Sean L Seymour; Lydia M Nuwaysir; Brent Lefebvre; Frank Kuhlmann; Joe Roark; Paape Rainer; Suckau Detlev; Tina Hemenway; Andreas Huhmer; James Langridge; Brian Connolly; Trey Chadick; Krisztina Holly; Josh Eckels; Eric W Deutsch; Robert L Moritz; Jonathan E Katz; David B Agus; Michael MacCoss; David L Tabb; Parag Mallick
Journal:  Nat Biotechnol       Date:  2012-10       Impact factor: 54.908

10.  GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data.

Authors:  Paulo C Carvalho; Juliana Sg Fischer; Emily I Chen; Gilberto B Domont; Maria Gc Carvalho; Wim M Degrave; John R Yates; Valmir C Barbosa
Journal:  Proteome Sci       Date:  2009-02-24       Impact factor: 2.480

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  59 in total

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Journal:  Proteomics       Date:  2020-04-02       Impact factor: 3.984

2.  A comprehensive proteogenomic study of the human Brucella vaccine strain 104 M.

Authors:  Xiaodong Zai; Qiaoling Yang; Kun Liu; Ruihua Li; Mengying Qian; Taoran Zhao; Yaohui Li; Ying Yin; Dayong Dong; Ling Fu; Shanhu Li; Junjie Xu; Wei Chen
Journal:  BMC Genomics       Date:  2017-05-23       Impact factor: 3.969

3.  The ribosome assembly factor Nop53 controls association of the RNA exosome with pre-60S particles in yeast.

Authors:  Leidy Paola P Cepeda; Felipe F M Bagatelli; Renata M Santos; Marlon D M Santos; Fabio C S Nogueira; Carla C Oliveira
Journal:  J Biol Chem       Date:  2019-10-29       Impact factor: 5.157

4.  Glycogen Metabolism Supports Photosynthesis Start through the Oxidative Pentose Phosphate Pathway in Cyanobacteria.

Authors:  Shrameeta Shinde; Xiaohui Zhang; Sonali P Singapuri; Isha Kalra; Xianhua Liu; Rachael M Morgan-Kiss; Xin Wang
Journal:  Plant Physiol       Date:  2019-10-24       Impact factor: 8.340

5.  Paip2 cooperates with Cbp80 at an active promoter and participates in RNA Polymerase II phosphorylation in Drosophila.

Authors:  Zaur M Kachaev; Lyubov A Lebedeva; Alexander V Shaposhnikov; James J Moresco; John R Yates; Paul Schedl; Yulii V Shidlovskii
Journal:  FEBS Lett       Date:  2019-04-29       Impact factor: 4.124

6.  Genomic and proteomic analysis of Tausonia pullulans reveals a key role for a GH15 glucoamylase in starch hydrolysis.

Authors:  Andrea Trochine; Nicolás Bellora; Paula Nizovoy; Rosario Duran; Gonzalo Greif; Virginia de García; Carlos Batthyany; Carlos Robello; Diego Libkind
Journal:  Appl Microbiol Biotechnol       Date:  2022-06-17       Impact factor: 4.813

7.  Integrated analysis of the sialotranscriptome and sialoproteome of the rat flea Xenopsylla cheopis.

Authors:  Stephen Lu; John F Andersen; Christopher F Bosio; B Joseph Hinnebusch; José M C Ribeiro
Journal:  J Proteomics       Date:  2022-01-04       Impact factor: 4.044

8.  Assessing the partners of the RBP9-mRNP complex in Trypanosoma cruzi using shotgun proteomics and RNA-seq.

Authors:  Helisa Helena Wippel; Alexandre Haruo Inoue; Newton Medeiros Vidal; Jimena Ferreira da Costa; Bruna Hilzendeger Marcon; Bruno Accioly Alves Romagnoli; Marlon Dias Mariano Santos; Paulo Costa Carvalho; Samuel Goldenberg; Lysangela Ronalte Alves
Journal:  RNA Biol       Date:  2018-09-10       Impact factor: 4.652

9.  Endothelial cell-specific redox gene modulation inhibits angiogenesis but promotes B16F0 tumor growth in mice.

Authors:  Yoshimitsu Yura; Brian S H Chong; Ryan D Johnson; Yosuke Watanabe; Yuko Tsukahara; Beatriz Ferran; Colin E Murdoch; Jessica B Behring; Mark E McComb; Catherine E Costello; Yvonne M W Janssen-Heininger; Richard A Cohen; Markus M Bachschmid; Reiko Matsui
Journal:  FASEB J       Date:  2019-10-26       Impact factor: 5.834

10.  Prospecting Biomarkers for Diagnostic and Therapeutic Approaches in Pythiosis.

Authors:  Jéssica Luana Chechi; Tiwa Rotchanapreeda; Giselle Souza da Paz; Ana Carolina Prado; Alana Lucena Oliveira; José Cavalcante Souza Vieira; Marília Afonso Rabelo Buzalaf; Anderson Messias Rodrigues; Lucilene Delazari Dos Santos; Theerapong Krajaejun; Sandra de Moraes Gimenes Bosco
Journal:  J Fungi (Basel)       Date:  2021-05-28
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