Evidence map›Paper›PMID 29470400›Full record

ArticleMetabolites2018

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

Bofei Zhang, Senyang Hu, Elizabeth Baskin, Andrew Patt, Jalal K Siddiqui, Ewy A Mathé

Abstract read
In one paragraph

Article in Metabolites, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Trial
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  5. Metabolite names and identifiers: how far are we from interoperability?Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Immunomodulatory metabolites in IgE-mediated food allergy and oral immunotherapy outcomes based on metabolomic profiling.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2024
    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

6 authors.

Bofei ZhangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. zhang.5675@buckeyemail.osu.edu.
Senyang HuDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. hu.993@buckeyemail.osu.edu.
Elizabeth BaskinDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. baskin.18@buckeyemail.osu.edu.
Andrew PattDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. patt.14@buckeyemail.osu.edu.
Jalal K SiddiquiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. Jalal.Siddiqui@osumc.edu.
Ewy A MathéDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA. ewy.mathe@osumc.edu.ORCID 0000-0003-4491-8107

Funding

Translational Therapeutics Research Program (TT)P30CA016058 · NCI · OHIO STATE UNIVERSITY · PI Tasleem J Padamsee · 1985 to 2026
$132.3M
Integrative Training in Biomedical SystemsT32GM068412 · NIGMS · OHIO STATE UNIVERSITY · PI PARVIN, JEFFREY D · 2005 to 2020
$2.4M
A comprehensive gene and metabolite pathway database for improving interpretation of metabolomics dataR03CA222428 · NCI · OHIO STATE UNIVERSITY · PI MATHE, EWY A · 2017 to 2017
$155k
NCI NIH HHS P30 CA016058NCI NIH HHS R03 CA222428NIGMS NIH HHS T32 GM068412
6 · The paper itself

Abstract

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

Indexed as

metabolomicspathway analysispathway databasetranscriptomics

Identifiers

PMID29470400
PMCPMC5876005

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.