ArticleProceedings of the National Academy of Sciences of the United States of America2000
Building a dictionary for genomes: identification of presumptive regulatory sites by statistical analysis.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 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
71 citing papers in PubMed, 1 synthesis or guideline pooled it, 258 citations in OpenAlex.
- Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data.BMC bioinformatics · 2006Pooled it
- Informational blueprints reveal condition-dependent gene regulatory architectures.bioRxiv : the preprint server for biology · 2026Article
- Species-aware DNA language models capture regulatory elements and their evolution.Genome biology · 2024Article
- MicrosatNavigator: exploring nonrandom distribution and lineage-specificity of microsatellite repeat motifs on vertebrate sex chromosomes across 186 whole genomes.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2023Article
- A lexical approach for identifying behavioural action sequences.PLoS computational biology · 2022Article
- Application of Transcriptional Gene Modules to Analysis ofG3 (Bethesda, Md.) · 2020Article
- Computational design of probes to detect bacterial genomes by multivalent binding.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Hierarchical compression of Caenorhabditis elegans locomotion reveals phenotypic differences in the organization of behaviour.Journal of the Royal Society, Interface · 2016Article
- On the unsupervised analysis of domain-specific Chinese texts.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- An Overview of NCA-Based Algorithms for Transcriptional Regulatory Network Inference.Microarrays (Basel, Switzerland) · 2015Review
- Comparative analysis of DNA word abundances in four yeast genomes using a novel statistical background model.PloS one · 2013Article
- Nucleosome free regions in yeast promoters result from competitive binding of transcription factors that interact with chromatin modifiers.PLoS computational biology · 2013Article
- Motif analysis unveils the possible co-regulation of chloroplast genes and nuclear genes encoding chloroplast proteins.Plant molecular biology · 2012Article
- Profile of Eric D. Siggia. Interview by Farooq Ahmed.Proceedings of the National Academy of Sciences of the United States of America · 2012Article
- CLARE: Cracking the LAnguage of Regulatory Elements.Bioinformatics (Oxford, England) · 2012Article
- GPUmotif: an ultra-fast and energy-efficient motif analysis program using graphics processing units.PloS one · 2012Article
- A motif-independent metric for DNA sequence specificity.BMC bioinformatics · 2011Article
- Article
- RecMotif: a novel fast algorithm for weak motif discovery.BMC bioinformatics · 2010Article
- Systematic identification of conserved motif modules in the human genome.BMC genomics · 2010Article
11 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
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The availability of complete genome sequences and mRNA expression data for all genes creates new opportunities and challenges for identifying DNA sequence motifs that control gene expression. An algorithm, "MobyDick," is presented that decomposes a set of DNA sequences into the most probable dictionary of motifs or words. This method is applicable to any set of DNA sequences: for example, all upstream regions in a genome or all genes expressed under certain conditions. Identification of words is based on a probabilistic segmentation model in which the significance of longer words is deduced from the frequency of shorter ones of various lengths, eliminating the need for a separate set of reference data to define probabilities. We have built a dictionary with 1,200 words for the 6, 000 upstream regulatory regions in the yeast genome; the 500 most significant words (some with as few as 10 copies in all of the upstream regions) match 114 of 443 experimentally determined sites (a significance level of 18 standard deviations). When analyzing all of the genes up-regulated during sporulation as a group, we find many motifs in addition to the few previously identified by analyzing the subclusters individually to the expression subclusters. Applying MobyDick to the genes derepressed when the general repressor Tup1 is deleted, we find known as well as putative binding sites for its regulatory partners.
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.