ArticleBriefings in bioinformatics2012
How to cluster gene expression dynamics in response to environmental signals.
Article in Briefings in bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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.
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.
Who cites it
32 citing papers in PubMed.
- Omnidirectional Interaction Networks Modulating Phenotypic Plasticity in the Gut Microbiota Towards Ulcerative Colitis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Statistical learning of stochastic complex systems via the Yau-Yau nonlinear filter.Innovation (Cambridge (Mass.)) · 2026Article
- An omnigenic interactome model to chart the genetic architecture of individual plants.Horticulture research · 2026Article
- Network stress: a wiring diagram of whole stress genes.Horticulture research · 2026Article
- Genome-Wide Network Analysis of Above- and Below-Ground Co-growth inPlant phenomics (Washington, D.C.) · 2024Article
- Predicting 1-year in-stent restenosis in superficial femoral arteries through multiscale computational modelling.Journal of the Royal Society, Interface · 2023Article
- A predictive multiscale model of in-stent restenosis in femoral arteries: linking haemodynamics and gene expression with an agent-based model of cellular dynamics.Journal of the Royal Society, Interface · 2022Article
- Vaginal microbiota networks as a mechanistic predictor of aerobic vaginitis.Frontiers in microbiology · 2022Article
- An eco-evo-devo genetic network model of stress response.Horticulture research · 2022Article
- Review
- FunGraph: A statistical protocol to reconstruct omnigenic multilayer interactome networks for complex traits.STAR protocols · 2021Article
- Inferring multilayer interactome networks shaping phenotypic plasticity and evolution.Nature communications · 2021Article
- Article
- A Multilayer Interactome Network Constructed in a Forest Poplar Population Mediates the Pleiotropic Control of Complex Traits.Frontiers in genetics · 2021Article
- Gene-Environment Interaction: A Variable Selection Perspective.Methods in molecular biology (Clifton, N.J.) · 2021Review
- Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph.Forestry research · 2021Review
- SEGN: Inferring real-time gene networks mediating phenotypic plasticity.Computational and structural biotechnology journal · 2020Article
- Article
- An omnidirectional visualization model of personalized gene regulatory networks.NPJ systems biology and applications · 2019Article
- G9a regulates temporal preimplantation developmental program and lineage segregation in blastocyst.eLife · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Organisms usually cope with change in the environment by altering the dynamic trajectory of gene expression to adjust the complement of active proteins. The identification of particular sets of genes whose expression is adaptive in response to environmental changes helps to understand the mechanistic base of gene-environment interactions essential for organismic development. We describe a computational framework for clustering the dynamics of gene expression in distinct environments through Gaussian mixture fitting to the expression data measured at a set of discrete time points. We outline a number of quantitative testable hypotheses about the patterns of dynamic gene expression in changing environments and gene-environment interactions causing developmental differentiation. The future directions of gene clustering in terms of incorporations of the latest biological discoveries and statistical innovations are discussed. We provide a set of computational tools that are applicable to modeling and analysis of dynamic gene expression data measured in multiple environments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.