Evidence map›Paper›PMID 42420737›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Quantitative Coarse-Grained Modeling of Microbial Metabolism: Uncovering Growth Laws, Environmental Responses, and Host-Circuit Coupling.

Yi-Hui Lai, Ting Lu

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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

2 authors.

Yi-Hui LaiDOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana, IL, USA.
Ting LuDOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, Urbana, IL, USA. luting@illinois.edu.

Funding

Integrative Circuit-Host Modeling of Synthetic Gene NetworksR35GM133579 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI LU, TING · 2019 to 2023
$1.9M
NIGMS NIH HHS R35 GM133579
6 · The paper itself

Abstract

Microbial cell metabolism is highly complex, involving a vast number of molecular species and multi-level regulatory processes. To address this complexity and decode cellular behavior, coarse-grained modeling provides a powerful quantitative framework by grouping similar biological entities while preserving essential network properties. This approach offers insights into intracellular regulation and resource allocation, enables systematic analysis of natural biological systems, and generates predictions for synthetic engineering outcomes. In this chapter, we present a comprehensive overview of coarse-grained modeling, from model construction to applications, and demonstrate its utility in uncovering microbial metabolic behavior.

Indexed as

BacteriaMetabolic Networks and PathwaysModels, BiologicalCoarse-grained modelingHost-circuit couplingKinetic modelingMathematical modelingMetabolic burdenMetabolic responseNutrient limitationProteome allocationResource allocation

Identifiers

PMID42420737
PMCPMC13629417

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.