Evidence map›Paper›PMID 36471236›Full record

ArticleThe journal of physical chemistry. B2022

What Makes a Functional Gene Regulatory Network? A Circuit Motif Analysis.

Lijia Huang, Benjamin Clauss, Mingyang Lu

Open access · greenAbstract read
In one paragraph

Article in The journal of physical chemistry. B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 40% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Lijia HuangCenter for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts02115, United States.
Benjamin ClaussCenter for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts02115, United States.
Mingyang LuCenter for Theoretical Biological Physics, Northeastern University, Boston, Massachusetts02115, United States.ORCID 0000-0001-8158-0593
Tufts University · USNortheastern University · US

Funding

New Computational Systems Biology Methods for Modeling Gene Regulatory CircuitsR35GM128717 · NIGMS · NORTHEASTERN UNIVERSITY · PI Mingyang Lu · 2018 to 2026
$3.3M
NIGMS NIH HHS R35 GM128717
6 · The paper itself

Abstract

One of the key questions in systems biology is to understand the roles of gene regulatory circuits in determining cellular states and their functions. In previous studies, some researchers have inferred large gene networks from genome wide genomics/transcriptomics data using the top-down approach, while others have modeled core gene circuits of small sizes using the bottom-up approach. Despite many existing systems biology studies, there is still no general rule on what sizes of gene networks and what types of circuit motifs a system would need to achieve robust biological functions. Here, we adopt a gene circuit motif analysis to discover four-node circuits responsible for multiplicity (rich in dynamical behavior), flexibility (versatile to alter gene expression), or both. We identify the most reoccurring two-node circuit motifs and the co-occurring motif pairs. Furthermore, we investigate the contributing factors of multiplicity and flexibility for large gene networks of different types and sizes. We find that gene networks of intermediate sizes tend to have combined high levels of multiplicity and flexibility. Our study will contribute to a better understanding of the dynamical mechanisms of gene regulatory circuits and provide insights into rational designs of robust gene circuits in synthetic and systems biology.

Indexed as

Gene Regulatory NetworksSystems Biology

Identifiers

PMID36471236
PMCPMC9896654
OpenAlexW4311665222

What OpenQuestion holds

Textmetadata
LicenceTDM
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.