ArticlePloS one2009
An integrated approach to identifying cis-regulatory modules in the human genome.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Towards a map of cis-regulatory sequences in the human genome.Nucleic acids research · 2018Article
- High resolution mapping of enhancer-promoter interactions.PloS one · 2015Article
- Article
- Overlapping chromatin-remodeling systems collaborate genome wide at dynamic chromatin transitions.Nature structural & molecular biology · 2014Article
- RFECS: a random-forest based algorithm for enhancer identification from chromatin state.PLoS computational biology · 2013Article
- Epigenetic priors for identifying active transcription factor binding sites.Bioinformatics (Oxford, England) · 2012Article
- Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.Nucleic acids research · 2011Article
- Genome Surveyor 2.0: cis-regulatory analysis in Drosophila.Nucleic acids research · 2011Article
- LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data.Nucleic acids research · 2011Article
- Quantitative models of the mechanisms that control genome-wide patterns of transcription factor binding during early Drosophila development.PLoS genetics · 2011Article
- Chromatin immunoprecipitation in adult zebrafish red cells.Methods in cell biology · 2011Article
- is-rSNP: a novel technique for in silico regulatory SNP detection.Bioinformatics (Oxford, England) · 2010Article
- Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites.Bioinformatics (Oxford, England) · 2010Article
- Quantitative analysis of the Drosophila segmentation regulatory network using pattern generating potentials.PLoS biology · 2010Article
- Construction of gene/transcription regulatory networks.Briefings in functional genomics · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In eukaryotic genomes, it is challenging to accurately determine target sites of transcription factors (TFs) by only using sequence information. Previous efforts were made to tackle this task by considering the fact that TF binding sites tend to be more conserved than other functional sites and the binding sites of several TFs are often clustered. Recently, ChIP-chip and ChIP-sequencing experiments have been accumulated to identify TF binding sites as well as survey the chromatin modification patterns at the regulatory elements such as promoters and enhancers. We propose here a hidden Markov model (HMM) to incorporate sequence motif information, TF-DNA interaction data and chromatin modification patterns to precisely identify cis-regulatory modules (CRMs). We conducted ChIP-chip experiments on four TFs, CREB, E2F1, MAX, and YY1 in 1% of the human genome. We then trained a hidden Markov model (HMM) to identify the labels of the CRMs by incorporating the sequence motifs recognized by these TFs and the ChIP-chip ratio. Chromatin modification data was used to predict the functional sites and to further remove false positives. Cross-validation showed that our integrated HMM had a performance superior to other existing methods on predicting CRMs. Incorporating histone signature information successfully penalized false prediction and improved the whole performance. The dataset we used and the software are available at http://nash.ucsd.edu/CIS/.
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.