Evidence map›Paper›PMID 41959107›Full record

ArticlebioRxiv : the preprint server for biology2026

From genes to collective modes: biological constraints shape metabolic evolution.

Aedan Brown, Sarah Datta, Pankaj Mehta, Brian Cleary

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

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

4 authors.

Aedan BrownDept. of Biomedical Engineering, Boston University, Boston, MA 02215.ORCID 0009-0008-2138-7490
Sarah DattaDept. of Mathematics, Boston Univeristy, Boston, MA 02215.
Pankaj MehtaDept. of Physics, Boston University, Boston MA 02215.ORCID 0000-0003-1290-5897
Brian ClearyDept. of Biomedical Engineering, Boston University, Boston, MA 02215.

Funding

MODELING EMERGENT BEHAVIORS IN SYSTEMS BIOLOGY: A BIOLOGICAL PHYSICS APPROACHR35GM119461 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Pankaj Mehta · 2016 to 2026
$3.6M
Training Program in Quantitative Biology & Physiology (QBP)T32GM145455 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Darren Michael Roblyer · 2022 to 2026
$2.6M
NIGMS NIH HHS R35 GM119461NIGMS NIH HHS T32 GM145455
6 · The paper itself

Abstract

Population genetics has been successful in explaining how drift, selection, and mutation shape allele frequencies. However, we still lack an understanding of how biological and evolutionary constraints arising from genotype-phenotype maps shape evolutionary dynamics. To explore this question, we developed a new framework for simulating the evolution of an inherently polygenic and epistatic trait - metabolism - combining population genetics with flux balance analysis. We found that the evolution of metabolic networks exhibits surprisingly simple, reproducible dynamics. We identify evolutionary collective modes (EvCMs) - linear combinations of genes with high, constant selective pressure - as organizers of the long-term dynamics and the origin of this simplicity. EvCMs arise through the interaction of physical constraints, evolvability, and the requirements for growth. We developed a theoretical framework to predict EvCMs from large-scale metabolic models and found quantitative agreement between theory and simulation of

Indexed as

collective modeevolutionmetabolism

Identifiers

PMID41959107
PMCPMC13060821

What OpenQuestion holds

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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.