Evidence map›Paper›PMID 27098040›Full record

ArticleNucleic acids research2016

GAM: a web-service for integrated transcriptional and metabolic network analysis.

Alexey A Sergushichev, Alexander A Loboda, Abhishek K Jha, Emma E Vincent, Edward M Driggers, Russell G Jones, Edward J Pearce, Maxim N Artyomov

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Alexey A SergushichevComputer Technologies Department, ITMO University, Saint Petersburg, 197101, Russia Department of Pathology & Immunology, Washington University in St. Louis, St.Louis, MO 63110, USA alsergbox@gmail.com.ORCID 0000-0003-1159-7220
Alexander A LobodaComputer Technologies Department, ITMO University, Saint Petersburg, 197101, Russia.
Abhishek K JhaAgios Pharmaceuticals, Cambridge, MA 02139, USA.
Emma E VincentGoodman Cancer Research Centre, McGill University, Montreal, QC H3A 1A3, Canada Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada.
Edward M DriggersGeneral Metabolics, Winchester, MA 01890, USA.
Russell G JonesGoodman Cancer Research Centre, McGill University, Montreal, QC H3A 1A3, Canada Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada.
Edward J PearceDepartment of Immunometabolism, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, D-79108, Germany.
Maxim N ArtyomovComputer Technologies Department, ITMO University, Saint Petersburg, 197101, Russia Department of Pathology & Immunology, Washington University in St. Louis, St.Louis, MO 63110, USA martyomov@pathology.wustl.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM ('genes and metabolites'): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/.

Indexed as

AlgorithmsSoftwareTranscription, GeneticAnimalsArabidopsisCell Line, TumorComputer GraphicsDatabases, GeneticEpithelial CellsHumansInternetMacrophage ActivationMacrophagesMetabolic Networks and PathwaysMetabolomeMice

Identifiers

PMID27098040
PMCPMC4987878

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.