Literature DB >> 30184047

metaGraphite-a new layer of pathway annotation to get metabolite networks.

Gabriele Sales1, Enrica Calura1, Chiara Romualdi1.   

Abstract

MOTIVATION: Metabolomics is an emerging 'omics' science involving the characterization of metabolites and metabolism in biological systems. Few bioinformatic tools have been developed for the visualization, exploration and analysis of metabolomic data within the context of metabolic pathways: some of them became rapidly obsolete and are no longer supported, others are based on a single database. A systematic collection of existing annotations has the potential of considerably boosting the investigation and contextualization of metabolomic measurements.
RESULTS: We have released a major update of our Bioconductor package graphite which explicitly tracks small molecules within pathway topologies and their interactions with proteins. The package gathers the information stored in eight major databases, oriented both at genes and at metabolites, across 14 different species. Depending on user preferences, all pathways can be retrieved as gene-only, gene metabolite or metabolite-only networks.
AVAILABILITY AND IMPLEMENTATION: The new graphite version (1.24) is available on Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2019        PMID: 30184047     DOI: 10.1093/bioinformatics/bty719

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


  6 in total

1.  MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules.

Authors:  Paolo Martini; Monica Chiogna; Enrica Calura; Chiara Romualdi
Journal:  Nucleic Acids Res       Date:  2019-08-22       Impact factor: 16.971

2.  SourceSet: A graphical model approach to identify primary genes in perturbed biological pathways.

Authors:  Elisa Salviato; Vera Djordjilović; Monica Chiogna; Chiara Romualdi
Journal:  PLoS Comput Biol       Date:  2019-10-25       Impact factor: 4.475

3.  Transcriptional Characterization of Stage I Epithelial Ovarian Cancer: A Multicentric Study.

Authors:  Enrica Calura; Matteo Ciciani; Andrea Sambugaro; Lara Paracchini; Giuseppe Benvenuto; Salvatore Milite; Paolo Martini; Luca Beltrame; Flaminia Zane; Robert Fruscio; Martina Delle Marchette; Fulvio Borella; Germana Tognon; Antonella Ravaggi; Dionyssios Katsaros; Eliana Bignotti; Franco Odicino; Maurizio D'Incalci; Sergio Marchini; Chiara Romualdi
Journal:  Cells       Date:  2019-12-01       Impact factor: 6.600

4.  Computational analysis to repurpose drugs for COVID-19 based on transcriptional response of host cells to SARS-CoV-2.

Authors:  Fuhai Li; Andrew P Michelson; Randi Foraker; Ming Zhan; Philip R O Payne
Journal:  BMC Med Inform Decis Mak       Date:  2021-01-07       Impact factor: 2.796

5.  DysPIA: A Novel Dysregulated Pathway Identification Analysis Method.

Authors:  Limei Wang; Weixin Xie; Kongning Li; Zhenzhen Wang; Xia Li; Weixing Feng; Jin Li
Journal:  Front Genet       Date:  2021-07-05       Impact factor: 4.599

Review 6.  The metaRbolomics Toolbox in Bioconductor and beyond.

Authors:  Jan Stanstrup; Corey D Broeckling; Rick Helmus; Nils Hoffmann; Ewy Mathé; Thomas Naake; Luca Nicolotti; Kristian Peters; Johannes Rainer; Reza M Salek; Tobias Schulze; Emma L Schymanski; Michael A Stravs; Etienne A Thévenot; Hendrik Treutler; Ralf J M Weber; Egon Willighagen; Michael Witting; Steffen Neumann
Journal:  Metabolites       Date:  2019-09-23
  6 in total

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