ArticleGenome biology2007
Clustering of genes into regulons using integrated modeling-COGRIM.
Article in Genome biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 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
31 citing papers in PubMed, 61 citations in OpenAlex.
- BINDER: computationally inferring a gene regulatory network for Mycobacterium abscessus.BMC bioinformatics · 2019Article
- Markov chain Monte Carlo simulation of a Bayesian mixture model for gene network inference.Genes & genomics · 2019Article
- CRNET: an efficient sampling approach to infer functional regulatory networks by integrating large-scale ChIP-seq and time-course RNA-seq data.Bioinformatics (Oxford, England) · 2018Article
- An integrative method to decode regulatory logics in gene transcription.Nature communications · 2017Article
- High-Throughput Identification of Cis-Regulatory Rewiring Events in Yeast.Molecular biology and evolution · 2015Article
- Semiparametric Bayes local additive models for longitudinal data.Statistics in biosciences · 2015Article
- Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response.Frontiers in genetics · 2013Article
- Unraveling regulatory programs for NF-kappaB, p53 and microRNAs in head and neck squamous cell carcinoma.PloS one · 2013Article
- Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection.BMC bioinformatics · 2013Article
- Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic.Bioinformatics (Oxford, England) · 2012Article
- Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.Scientific reports · 2012Article
- LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data.Nucleic acids research · 2011Article
- Transcriptional regulation via TF-modifying enzymes: an integrative model-based analysis.Nucleic acids research · 2011Article
- Motif-guided sparse decomposition of gene expression data for regulatory module identification.BMC bioinformatics · 2011Article
- Inferring a transcriptional regulatory network from gene expression data using nonlinear manifold embedding.PloS one · 2011Article
- TF-centered downstream gene set enrichment analysis: Inference of causal regulators by integrating TF-DNA interactions and protein post-translational modifications information.BMC bioinformatics · 2010Article
- Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model.Bioinformatics (Oxford, England) · 2010Article
- Multilevel support vector regression analysis to identify condition-specific regulatory networks.Bioinformatics (Oxford, England) · 2010Article
- Mimosa: mixture model of co-expression to detect modulators of regulatory interaction.Algorithms for molecular biology : AMB · 2010Article
- Correlated changes between regulatory cis elements and condition-specific expression in paralogous gene families.Nucleic acids research · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
We present a Bayesian hierarchical model and Gibbs Sampling implementation that integrates gene expression, ChIP binding, and transcription factor motif data in a principled and robust fashion. COGRIM was applied to both unicellular and mammalian organisms under different scenarios of available data. In these applications, we demonstrate the ability to predict gene-transcription factor interactions with reduced numbers of false-positive findings and to make predictions beyond what is obtained when single types of data are considered.
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.