PReMod -- a database of genome-wide mammalian cis-regulatory module predictions
What you can do:
Conduct genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes.
Highlights:
- This database is based on a prediction algorithm that exploits the fact that many known CRMs are made of clusters of phylogenetically conserved and repeated transcription factors (TF) binding sites.
- Contrary to other existing databases, PReMod is not restricted to modules located proximal to genes, but in fact mostly contains distal predicted CRMs (pCRMs).
- It allows users to:
- *identify pCRMs around a gene of interest
- *identify pCRMs that have binding sites for a given TF (or a set of TFs)
- *download the entire dataset for local analyses
- The output includes information about the binding sites predicted within the selected pCRMs, and a graphical display of their distribution within the pCRMs.
- It also provides a visual depiction of the chromosomal context of the selected pCRMs in terms of neighboring pCRMs and genes, all of which are linked to the UCSC Genome Browser and the NCBI.
Keywords:
- transcription factor binding site prediction tool
- transcription factor binding site analysis tool
- DNA-binding sites prediction tool
- cis-elements prediction tool
- cis-regulatory module prediction tool
- cis-regulatory elements prediction tool
- promoter analysis tool
- genome wide cis-regulatory module prediction tool
- promoter elements prediction tool
- combinational cis-regulatory elements
- transcription factors
- human transcription factor binding sites
- mouse transcription factor binding sites
- mammalian cis-regulatory modules
Literature & Tutorials:
PubMed Link: PReMod -- a database of genome-wide mammalian cis-regulatory module predictions
PubMed Link of prediction algorithms: Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression
PubMed Link of prediction algorithms: Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression
This record last updated: 03-21-2007