ArticleGenome research2010
Integrating multiple evidence sources to predict transcription factor binding in the human genome.
Article in Genome research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
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
63 citing papers in PubMed, 1 synthesis or guideline pooled it, 100 citations in OpenAlex.
- A systematic review of multimodal clinical biomarkers in the management of thyroid eye disease.Reviews in endocrine & metabolic disorders · 2022Pooled it
- Blood-based DNA methylation in advanced Nasopharyngeal Carcinoma exhibited distinct CpG methylation signature.Scientific reports · 2023Article
- An Evidence Theory and Fuzzy Logic Combined Approach for the Prediction of Potential ARF-Regulated Genes in Quinoa.Plants (Basel, Switzerland) · 2022Article
- Understanding pathogen-host interplay by expression profiles of lncRNA and mRNA in the liver of Echinococcus multilocularis-infected mice.PLoS neglected tropical diseases · 2022Article
- Construction of Condition-Specific Gene Regulatory Network Using Kernel Canonical Correlation Analysis.Frontiers in genetics · 2021Article
- Biomarker identification of thyroid associated ophthalmopathy using microarray data.International journal of ophthalmology · 2018Article
- Cancer cell line specific co-factors modulate the FOXM1 cistrome.Oncotarget · 2017Article
- MicroRNAs Induce a Permissive Chromatin Environment that Enables Neuronal Subtype-Specific Reprogramming of Adult Human Fibroblasts.Cell stem cell · 2017Article
- Three TF Co-expression Modules Regulate Pressure-Overload Cardiac Hypertrophy in Male Mice.Scientific reports · 2017Article
- Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility.BMC bioinformatics · 2017Article
- Estimating genome-wide regulatory activity from multi-omics data sets using mathematical optimization.BMC systems biology · 2017Article
- Imputation for transcription factor binding predictions based on deep learning.PLoS computational biology · 2017Article
- Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways.Bioinformatics (Oxford, England) · 2016Article
- Uncovering MicroRNA Regulatory Hubs that Modulate Plasma Cell Differentiation.Scientific reports · 2015Article
- A DNA shape-based regulatory score improves position-weight matrix-based recognition of transcription factor binding sites.Bioinformatics (Oxford, England) · 2015Article
- Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.PLoS computational biology · 2015Article
- i-cisTarget 2015 update: generalized cis-regulatory enrichment analysis in human, mouse and fly.Nucleic acids research · 2015Article
- SMARTS: reconstructing disease response networks from multiple individuals using time series gene expression data.Bioinformatics (Oxford, England) · 2015Article
- Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state.Nature communications · 2015Article
- Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.BMC bioinformatics · 2015Article
3 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
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Information about the binding preferences of many transcription factors is known and characterized by a sequence binding motif. However, determining regions of the genome in which a transcription factor binds based on its motif is a challenging problem, particularly in species with large genomes, since there are often many sequences containing matches to the motif but are not bound. Several rules based on sequence conservation or location, relative to a transcription start site, have been proposed to help differentiate true binding sites from random ones. Other evidence sources may also be informative for this task. We developed a method for integrating multiple evidence sources using logistic regression classifiers. Our method works in two steps. First, we infer a score quantifying the general binding preferences of transcription factor binding at all locations based on a large set of evidence features, without using any motif specific information. Then, we combined this general binding preference score with motif information for specific transcription factors to improve prediction of regions bound by the factor. Using cross-validation and new experimental data we show that, surprisingly, the general binding preference can be highly predictive of true locations of transcription factor binding even when no binding motif is used. When combined with motif information our method outperforms previous methods for predicting locations of true binding.
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.