ArticleeLife2020
Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 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
97 citing papers in PubMed.
- scYeast: a biological-knowledge-guided foundation model on yeast single-cell transcriptomics.Synthetic and systems biotechnology · 2027Article
- GLM-Prior: a genomic language model for transferable sequence-derived priors in gene regulatory network inference.Nature communications · 2026Article
- Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.Molecular systems biology · 2026Article
- Design of the biosensor-dependent coupling system stabilizes the high-synthesis phenotype of cell factory.Nature communications · 2026Article
- Single-cell analyses identify independent aging processes that compete to determine cellular fate in budding yeast.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Article
- Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation.Genome research · 2026Article
- Single cell profiling framework reveals metabolic subpopulations as drivers of bioproduction heterogeneity.Nature communications · 2025Article
- LogicSR: prior-guided symbolic regression for gene regulatory network inference from single-cell transcriptomics data.Briefings in bioinformatics · 2025Article
- Mapping the transcriptional regulatory network of a fungal pathogen by exploiting transcription factor perturbation.bioRxiv : the preprint server for biology · 2025Article
- Dissecting microbial communities with single-cell transcriptome analysis.Science (New York, N.Y.) · 2025Review
- Article
- A single-cell resolved genotype-phenotype map using genome-wide genetic and environmental perturbations.Nature communications · 2025Article
- Transcriptional heterogeneity shapes stress-adaptive responses in yeast.Nature communications · 2025Article
- Article
- Optimized network inference for immune diseased single cells.Frontiers in immunology · 2025Article
- NetREm: Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation.Bioinformatics advances · 2025Article
- Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction.bioRxiv : the preprint server for biology · 2024Article
- Bayesian inference of sample-specific coexpression networks.Genome research · 2024Article
- Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity.Nature communications · 2024Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Understanding how gene expression programs are controlled requires identifying regulatory relationships between transcription factors and target genes. Gene regulatory networks are typically constructed from gene expression data acquired following genetic perturbation or environmental stimulus. Single-cell RNA sequencing (scRNAseq) captures the gene expression state of thousands of individual cells in a single experiment, offering advantages in combinatorial experimental design, large numbers of independent measurements, and accessing the interaction between the cell cycle and environmental responses that is hidden by population-level analysis of gene expression. To leverage these advantages, we developed a method for scRNAseq in budding yeast (
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.