ReviewDie Naturwissenschaften2003
In silico identification of metazoan transcriptional regulatory regions.
Review in Die Naturwissenschaften, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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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.
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Who cites it
16 citing papers in PubMed, 33 citations in OpenAlex.
- Article
- Evaluating tools for transcription factor binding site prediction.BMC bioinformatics · 2016Article
- Identification of candidate transcription factor binding sites in the cattle genome.Genomics, proteomics & bioinformatics · 2013Article
- Article
- Assigning roles to DNA regulatory motifs using comparative genomics.Bioinformatics (Oxford, England) · 2010Article
- Recent computational approaches to understand gene regulation: mining gene regulation in silico.Current genomics · 2007Article
- In silico identification of NF-kappaB-regulated genes in pancreatic beta-cells.BMC bioinformatics · 2007Article
- A survey of motif discovery methods in an integrated framework.Biology direct · 2006Article
- oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes.Nucleic acids research · 2005Article
- Identification of the 'NORE' (N-Oct-3 responsive element), a novel structural motif and composite element.Nucleic acids research · 2005Article
- A novel approach to identifying regulatory motifs in distantly related genomes.Genome biology · 2005Article
- Lower rate of genomic variation identified in the trans-membrane domain of monoamine sub-class of Human G-Protein Coupled Receptors: the Human GPCR-DB Database.BMC genomics · 2004Article
- Decoding human regulatory circuits.Genome research · 2004Article
- ConSite: web-based prediction of regulatory elements using cross-species comparison.Nucleic acids research · 2004Article
- From sequence to structure and back again: approaches for predicting protein-DNA binding.Proteome science · 2004Article
- JASPAR: an open-access database for eukaryotic transcription factor binding profiles.Nucleic acids research · 2004Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcriptional regulation remains one of the most intriguing and challenging subjects in biomedical research. The catalysis of transcription is a clear example of multiple proteins interacting to orchestrate a biological process, offering a starting point for the study of biological systems. Transcriptional regulation is viewed as one of the principal mechanisms governing the spatial and temporal distribution of gene expression, thus the field of transcriptional regulation provides a natural stage for quantitative studies of multiple gene systems. Building on the body of focused experimental studies and new genomics-driven data, computational biologists are making significant strides in accelerating our understanding of the transcriptional regulatory process in metazoan cells. Recent advances in the computational analysis of the interplay between factors have been fueled by well-defined computational methods for the modeling of the binding of individual transcription factors. We present here an overview of advances in the analysis of regulatory systems and the fundamental methods that underlie the recent developments.
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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.