Evidence map›Paper›PMID 41415426›Full record

ArticlebioRxiv : the preprint server for biology2025

hypeR-GEM: connecting metabolite signatures to enzyme-coding genes via genome-scale metabolic models.

Ziwei Huang, Paola Sebastiani, Daniel Segrè, Stefano Monti

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ziwei HuangDepartment of Physics, Boston University, Boston, MA.ORCID 0009-0005-4879-8175
Paola SebastianiInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA.
Daniel SegrèDepartment of Physics, Boston University, Boston, MA.ORCID 0000-0003-4859-1914
Stefano MontiDivision of Computational Biomedicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA.ORCID 0000-0002-9376-0660

Funding

Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI Ryan Tewhey · 2004 to 2026
$102.6M
Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategiesUH3AG064704 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI PERLS, THOMAS T, SEBASTIANI, PAOLA · 2022 to 2025
$14.7M
System-Level Analyses of Multi-Omics Data to Reveal Mechanisms of Head & Neck CancerR01DE031831 · NIDCR · BOSTON UNIVERSITY MEDICAL CAMPUS · PI MONTI, STEFANO · 2022 to 2024
$1.3M
NIA NIH HHS U19 AG023122NIA NIH HHS UH3 AG064704NIDCR NIH HHS R01 DE031831
6 · The paper itself

Abstract

Enrichment analysis is a cornerstone of "omics" data interpretation, enabling researchers to connect analysis results to biological processes and generate testable hypotheses. While well-established tools exist for transcriptomics and other omics layers, the development of robust enrichment resources for metabolomics remains comparatively limited. To address this gap, we developed

Identifiers

PMID41415426
PMCPMC12710827

What OpenQuestion holds

Textmetadata
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.