ArticleNucleic acids research2004
Discovery of sequence motifs related to coexpression of genes using evolutionary computation.
Article in Nucleic acids research, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Fast and exact quantification of motif occurrences in biological sequences.BMC bioinformatics · 2021Article
- Sequence-based 5-mers highly correlated to epigenetic modifications in genes interactions.Genes & genomics · 2018Article
- Sequence motif finder using memetic algorithm.BMC bioinformatics · 2018Article
- Motif discovery and transcription factor binding sites before and after the next-generation sequencing era.Briefings in bioinformatics · 2013Article
- Discovering multiple realistic TFBS motifs based on a generalized model.BMC bioinformatics · 2009Article
- Relationship between gene co-expression and sharing of transcription factor binding sites in Drosophila melanogaster.Bioinformatics (Oxford, England) · 2009Article
- Evolutionary computation for discovery of composite transcription factor binding sites.Nucleic acids research · 2008Article
- Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms.BMC bioinformatics · 2007Article
- A survey of DNA motif finding algorithms.BMC bioinformatics · 2007Review
- Comparative analysis of regulatory motif discovery tools for transcription factor binding sites.Genomics, proteomics & bioinformatics · 2007Article
- Discovery, validation, and genetic dissection of transcription factor binding sites by comparative and functional genomics.Genome research · 2005Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcription factors are key regulatory elements that control gene expression. Recognition of transcription factor binding site (TFBS) motifs in the upstream region of coexpressed genes is therefore critical towards a true understanding of the regulations of gene expression. The task of discovering eukaryotic TFBSs remains a challenging problem. Here, we demonstrate that evolutionary computation can be used to search for TFBSs in upstream regions of genes known to be coexpressed. Evolutionary computation was used to search for TFBSs of genes regulated by octamer-binding factor and nuclear factor kappa B. The discovered binding sites included experimentally determined known binding motifs as well as lists of putative, previously unknown TFBSs. We believe that this method to search nucleotide sequence information efficiently for similar motifs will be useful for discovering TFBSs that affect gene regulation.
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.