Literature DB >> 29118029

Graphical Interpretation and Analysis of Proteins and their Ontologies (GiaPronto): A One-Click Graph Visualization Software for Proteomics Data Sets.

Amber K Weiner1,2,3, Simone Sidoli3, Sharon J Diskin1,2, Benjamin A Garcia4,3.   

Abstract

Here we present a free interactive web tool to process and visualize proteomics data sets with a single click. GiaPronto can process all proteomics quantification methods, i.e. label-free, SILAC and isobaric labeling, and analyze post-translational modifications (PTMs). The software performs normalization and statistics, assists determination of regulated proteins, biomarkers and Gene Ontology (GO) enrichment, and provides high resolution images and tables for further data analysis. We foresee that GiaPronto will become the most rapid and simple tool for assessing data quality and determining most relevant features of proteomic data sets. GiaPronto is available at giapronto.diskinlab.org.
© 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Keywords:  Algorithms; Bioinformatics software; Data Analysis; Data Visualization; Data standards; Label-free quantification; SILAC

Mesh:

Substances:

Year:  2017        PMID: 29118029      PMCID: PMC6030729          DOI: 10.1074/mcp.TIR117.000438

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  9 in total

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Authors:  Simone Sidoli; Lei Cheng; Ole N Jensen
Journal:  J Proteomics       Date:  2012-01-03       Impact factor: 4.044

2.  clusterProfiler: an R package for comparing biological themes among gene clusters.

Authors:  Guangchuang Yu; Li-Gen Wang; Yanyan Han; Qing-Yu He
Journal:  OMICS       Date:  2012-03-28

Review 3.  Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present.

Authors:  Marcus Bantscheff; Simone Lemeer; Mikhail M Savitski; Bernhard Kuster
Journal:  Anal Bioanal Chem       Date:  2012-07-08       Impact factor: 4.142

4.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

Authors:  Jürgen Cox; Matthias Mann
Journal:  Nat Biotechnol       Date:  2008-11-30       Impact factor: 54.908

Review 5.  Using R and Bioconductor for proteomics data analysis.

Authors:  Laurent Gatto; Andy Christoforou
Journal:  Biochim Biophys Acta       Date:  2013-05-18

6.  The Perseus computational platform for comprehensive analysis of (prote)omics data.

Authors:  Stefka Tyanova; Tikira Temu; Pavel Sinitcyn; Arthur Carlson; Marco Y Hein; Tamar Geiger; Matthias Mann; Jürgen Cox
Journal:  Nat Methods       Date:  2016-06-27       Impact factor: 28.547

7.  Time-resolved Global and Chromatin Proteomics during Herpes Simplex Virus Type 1 (HSV-1) Infection.

Authors:  Katarzyna Kulej; Daphne C Avgousti; Simone Sidoli; Christin Herrmann; Ashley N Della Fera; Eui Tae Kim; Benjamin A Garcia; Matthew D Weitzman
Journal:  Mol Cell Proteomics       Date:  2017-02-08       Impact factor: 5.911

8.  Highly selective enrichment of phosphorylated peptides using titanium dioxide.

Authors:  Tine E Thingholm; Thomas J D Jørgensen; Ole N Jensen; Martin R Larsen
Journal:  Nat Protoc       Date:  2006       Impact factor: 13.491

9.  High-performance hybrid Orbitrap mass spectrometers for quantitative proteome analysis: Observations and implications.

Authors:  James C Williamson; Alistair V G Edwards; Thiago Verano-Braga; Veit Schwämmle; Frank Kjeldsen; Ole N Jensen; Martin R Larsen
Journal:  Proteomics       Date:  2016-03-01       Impact factor: 3.984

  9 in total
  7 in total

1.  Simultaneous Improvement in the Precision, Accuracy, and Robustness of Label-free Proteome Quantification by Optimizing Data Manipulation Chains.

Authors:  Jing Tang; Jianbo Fu; Yunxia Wang; Yongchao Luo; Qingxia Yang; Bo Li; Gao Tu; Jiajun Hong; Xuejiao Cui; Yuzong Chen; Lixia Yao; Weiwei Xue; Feng Zhu
Journal:  Mol Cell Proteomics       Date:  2019-05-16       Impact factor: 5.911

2.  Methamphetamine Dysregulates Macrophage Functions and Autophagy to Mediate HIV Neuropathogenesis.

Authors:  John M Barbaro; Simone Sidoli; Ana Maria Cuervo; Joan W Berman
Journal:  Biomedicines       Date:  2022-05-27

3.  ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data.

Authors:  Wasim Aftab; Shibojyoti Lahiri; Axel Imhof
Journal:  Mol Cell Proteomics       Date:  2022-05-13       Impact factor: 7.381

4.  ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies.

Authors:  Jing Tang; Jianbo Fu; Yunxia Wang; Bo Li; Yinghong Li; Qingxia Yang; Xuejiao Cui; Jiajun Hong; Xiaofeng Li; Yuzong Chen; Weiwei Xue; Feng Zhu
Journal:  Brief Bioinform       Date:  2020-03-23       Impact factor: 11.622

5.  PANDA-view: an easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

Authors:  Cheng Chang; Kaikun Xu; Chaoping Guo; Jinxia Wang; Qi Yan; Jian Zhang; Fuchu He; Yunping Zhu
Journal:  Bioinformatics       Date:  2018-10-15       Impact factor: 6.937

6.  OmicsOne: associate omics data with phenotypes in one-click.

Authors:  Hui Zhang; Minghui Ao; Arianna Boja; Michael Schnaubelt; Yingwei Hu
Journal:  Clin Proteomics       Date:  2021-12-11       Impact factor: 3.988

Review 7.  Plant Antimicrobial Peptides: State of the Art, In Silico Prediction and Perspectives in the Omics Era.

Authors:  Carlos André Dos Santos-Silva; Luisa Zupin; Marx Oliveira-Lima; Lívia Maria Batista Vilela; João Pacifico Bezerra-Neto; José Ribamar Ferreira-Neto; José Diogo Cavalcanti Ferreira; Roberta Lane de Oliveira-Silva; Carolline de Jesús Pires; Flavia Figueira Aburjaile; Marianne Firmino de Oliveira; Ederson Akio Kido; Sergio Crovella; Ana Maria Benko-Iseppon
Journal:  Bioinform Biol Insights       Date:  2020-09-02
  7 in total

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