ArticleGenome biology2006
The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo.
Article in Genome biology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 269 papers.
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Who cites it
269 citing papers in PubMed.
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- PARROT: Phase-Altering Regulatory Rewiring Over Time.bioRxiv : the preprint server for biology · 2026Article
- Computational blueprints for cell fate programming.Stem cell reports · 2026Review
- Gene regulatory network determinants of rapid recall in human memory CD4Cell reports · 2026Article
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- Data-driven discovery of digital twins in biomedical research.Briefings in bioinformatics · 2026Review
- GeneSNAKE: a Python package for simulation of gene regulatory networks and perturbation-induced expression data.Bioinformatics advances · 2026Article
- Evolution of the Cell-Cycle Clock Models: Biochemical or Transcriptional?Advances in experimental medicine and biology · 2026Review
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- 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
- Machine learning methods for gene regulatory network inference.Briefings in bioinformatics · 2025Review
- Growth-limiting drought increases sensitivity of Asian rice (Oryza sativa) leaves to heat shock through physiological and spatially distinct transcriptomic responses.The Plant journal : for cell and molecular biology · 2025Article
- A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data.Briefings in bioinformatics · 2024Review
- Reverse network diffusion to remove indirect noise for better inference of gene regulatory networks.Bioinformatics (Oxford, England) · 2024Article
- Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.BioEssays : news and reviews in molecular, cellular and developmental biology · 2024Review
- Structure-primed embedding on the transcription factor manifold enables transparent model architectures for gene regulatory network and latent activity inference.Genome biology · 2024Article
- Modeling transcriptional regulation of the cell cycle using a novel cybernetic-inspired approach.Biophysical journal · 2024Article
- Inferring Dynamic Regulatory Interaction Graphs from Time Series Data with Perturbations.Proceedings of machine learning research · 2024Article
209 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
We present a method (the Inferelator) for deriving genome-wide transcriptional regulatory interactions, and apply the method to predict a large portion of the regulatory network of the archaeon Halobacterium NRC-1. The Inferelator uses regression and variable selection to identify transcriptional influences on genes based on the integration of genome annotation and expression data. The learned network successfully predicted Halobacterium's global expression under novel perturbations with predictive power similar to that seen over training data. Several specific regulatory predictions were experimentally tested and verified.
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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.