ArticleBMC bioinformatics2005
Using hexamers to predict cis-regulatory motifs in Drosophila.
Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 61 citations in OpenAlex.
- Trial
- BestCRM: An Exhaustive Search for Optimal Cis-Regulatory Modules in Promoters Accelerated by the Multidimensional Hash Function.International journal of molecular sciences · 2024Article
- Exploring objective feature sets in constructing the evolution relationship of animal genome sequences.BMC genomics · 2023Article
- Intrinsic laws of k-mer spectra of genome sequences and evolution mechanism of genomes.BMC evolutionary biology · 2020Article
- MiPepid: MicroPeptide identification tool using machine learning.BMC bioinformatics · 2019Article
- Evolutionary mechanism and biological functions of 8-mers containing CG dinucleotide in yeast.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2017Article
- Article
- Article
- Imogene: identification of motifs and cis-regulatory modules underlying gene co-regulation.Nucleic acids research · 2014Article
- Computational tools and resources for prediction and analysis of gene regulatory regions in the chick genome.Genesis (New York, N.Y. : 2000) · 2013Review
- A statistical thin-tail test of predicting regulatory regions in the Drosophila genome.Theoretical biology & medical modelling · 2013Article
- Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison.Nucleic acids research · 2011Article
- Eukaryotic and prokaryotic promoter prediction using hybrid approach.Theory in biosciences = Theorie in den Biowissenschaften · 2011Article
- Assessing computational methods of cis-regulatory module prediction.PLoS computational biology · 2010Article
- An alignment-free method to identify candidate orthologous enhancers in multiple Drosophila genomes.Bioinformatics (Oxford, England) · 2010Article
- Genome-wide identification of cis-regulatory motifs and modules underlying gene coregulation using statistics and phylogeny.Proceedings of the National Academy of Sciences of the United States of America · 2010Article
- Motif-blind, genome-wide discovery of cis-regulatory modules in Drosophila and mouse.Developmental cell · 2009Article
- Article
- Identifying regulatory elements in eukaryotic genomes.Briefings in functional genomics & proteomics · 2009Review
- Finding evolutionarily conserved cis-regulatory modules with a universal set of motifs.BMC bioinformatics · 2009Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundCis-regulatory modules (CRMs) are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered.
resultsWe present a simple, efficient method (HexDiff) based only on hexamer frequencies of known CRMs and non-CRM sequence to predict novel CRMs in regulatory systems. On a data set of 16 gap and pair-rule genes containing 52 known CRMs, predictions made by HexDiff had a higher correlation with the known CRMs than several existing CRM prediction algorithms: Ahab, Cluster Buster, MSCAN, MCAST, and LWF. After combining the results of the different algorithms, 10 putative CRMs were identified and are strong candidates for future study. The hexamers used by HexDiff to distinguish between CRMs and non-CRM sequence were also analyzed and were shown to be enriched in regulatory elements.
conclusionHexDiff provides an efficient and effective means for finding new CRMs based on known CRMs, rather than known binding sites.
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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.