ArticleBMC genomics2014
TACO: a general-purpose tool for predicting cell-type-specific transcription factor dimers.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed.
- Article
- Asymmetry of Motif Conservation Within Their Homotypic Pairs Distinguishes DNA-Binding Domains of Target Transcription Factors in ChIP-Seq Data.International journal of molecular sciences · 2025Article
- A new pipeline SPICE identifies novel JUN-IKZF1 composite elements.bioRxiv : the preprint server for biology · 2024Article
- Identification of transcription factor co-binding patterns with non-negative matrix factorization.Nucleic acids research · 2024Article
- Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks.International journal of molecular sciences · 2024Article
- Web-MCOT Server for Motif Co-Occurrence Search in ChIP-Seq Data.International journal of molecular sciences · 2022Article
- TF-COMB - Discovering grammar of transcription factor binding sites.Computational and structural biotechnology journal · 2022Article
- Evidence of widespread, independent sequence signature for transcription factor cobinding.Genome research · 2021Article
- NAUTICA: classifying transcription factor interactions by positional and protein-protein interaction information.Biology direct · 2020Article
- Asymmetric Conservation within Pairs of Co-Occurred Motifs Mediates Weak Direct Binding of Transcription Factors in ChIP-Seq Data.International journal of molecular sciences · 2020Article
- MODER2: first-order Markov modeling and discovery of monomeric and dimeric binding motifs.Bioinformatics (Oxford, England) · 2020Article
- Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions.Nature communications · 2020Article
- Motif grammar: The basis of the language of gene expression.Computational and structural biotechnology journal · 2020Review
- A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package.Nucleic acids research · 2019Article
- TICA: Transcriptional Interaction and Coregulation Analyzer.Genomics, proteomics & bioinformatics · 2018Article
- coTRaCTE predicts co-occurring transcription factors within cell-type specific enhancers.PLoS computational biology · 2018Article
- DNA-mediated dimerization on a compact sequence signature controls enhancer engagement and regulation by FOXA1.Nucleic acids research · 2018Article
- Modular discovery of monomeric and dimeric transcription factor binding motifs for large data sets.Nucleic acids research · 2018Article
- Removing Background Co-occurrences of Transcription Factor Binding Sites Greatly Improves the Prediction of Specific Transcription Factor Cooperations.Frontiers in genetics · 2018Article
- Romulus: robust multi-state identification of transcription factor binding sites from DNase-seq data.Bioinformatics (Oxford, England) · 2016Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCooperative binding of transcription factor (TF) dimers to DNA is increasingly recognized as a major contributor to binding specificity. However, it is likely that the set of known TF dimers is highly incomplete, given that they were discovered using ad hoc approaches, or through computational analyses of limited datasets.
resultsHere, we present TACO (Transcription factor Association from Complex Overrepresentation), a general-purpose standalone software tool that takes as input any genome-wide set of regulatory elements and predicts cell-type-specific TF dimers based on enrichment of motif complexes. TACO is the first tool that can accommodate motif complexes composed of overlapping motifs, a characteristic feature of many known TF dimers. Our method comprehensively outperforms existing tools when benchmarked on a reference set of 29 known dimers. We demonstrate the utility and consistency of TACO by applying it to 152 DNase-seq datasets and 94 ChIP-seq datasets.
conclusionsBased on these results, we uncover a general principle governing the structure of TF-TF-DNA ternary complexes, namely that the flexibility of the complex is correlated with, and most likely a consequence of, inter-motif spacing.
Indexed as
Identifiers
What Socratic 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 Socratic graph.