Evidence map›Paper›PMID 33667112›Full record

ReviewAnnual review of plant biology2021

Time-Based Systems Biology Approaches to Capture and Model Dynamic Gene Regulatory Networks.

Jose M Alvarez, Matthew D Brooks, Joseph Swift, Gloria M Coruzzi

Abstract readReview
In one paragraph

Review in Annual review of plant biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  5. OsNRT1.1B-OsCNGC14/16-CaAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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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

4 authors.

Jose M AlvarezCentro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, Chile.
Matthew D BrooksGlobal Change and Photosynthesis Research Unit, US Department of Agriculture Agricultural Research Service, Urbana, Illinois 61801, USA.
Joseph SwiftSalk Institute for Biological Studies, La Jolla, California 92037, USA.
Gloria M CoruzziCenter for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA; email: gc2@nyu.edu.

Funding

Hit-and-Run transcription: The impact of transient interactions in dynamic gene regulatory networks that mediate rapid nutrient signalingR01GM121753 · NIGMS · NEW YORK UNIVERSITY · PI CORUZZI, GLORIA, SHASHA, DENNIS ELLIOTT · 2020 to 2023
$1.7M
Uncovering the molecular basis for dynamic regulatory networks in plantsF32GM116347 · NIGMS · NEW YORK UNIVERSITY · PI BROOKS, MATTHEW D · 2016 to 2017
$121k
NIGMS NIH HHS F32 GM116347NIGMS NIH HHS R01 GM121753
6 · The paper itself

Abstract

All aspects of transcription and its regulation involve dynamic events. However, capturing these dynamic events in gene regulatory networks (GRNs) offers both a promise and a challenge. The promise is that capturing and modeling the dynamic changes in GRNs will allow us to understand how organisms adapt to a changing environment. The ability to mount a rapid transcriptional response to environmental changes is especially important in nonmotile organisms such as plants. The challenge is to capture these dynamic, genome-wide events and model them in GRNs. In this review, we cover recent progress in capturing dynamic interactions of transcription factors with their targets-at both the local and genome-wide levels-and how they are used to learn how GRNs operate as a function of time. We also discuss recent advances that employ time-based machine learning approaches to forecast gene expression at future time points, a key goal of systems biology.

Indexed as

Gene Regulatory NetworksSystems BiologyComputational BiologyPlantsTranscription FactorsTranscription Factorsdynamic network modelinggene regulatory networkssystems biologytime-based genome-wide studiestranscription factortransient regulatory events

Identifiers

PMID33667112
PMCPMC9312366

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.