Linked Life Data

21431758

Source:http://linkedlifedata.com/resource/pubmed/id/21431758

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2011-3-24
pubmed:abstractText
mRNA molecules are tightly regulated, mostly through interactions with proteins and other RNAs, but the mechanisms that confer the specificity of such interactions are poorly understood. It is clear, however, that this specificity is determined by both the nucleotide sequence and secondary structure of the mRNA. We developed RNApromo, an efficient computational tool for identifying structural elements within mRNAs that are involved in specifying post-transcriptional regulations. Using RNApromo, we predicted putative motifs in sets of mRNAs with substantial experimental evidence for common post-transcriptional regulation, including mRNAs with similar decay rates, mRNAs that are bound by the same RNA binding protein, and mRNAs with a common cellular localization. Our new RNA motif discovery tool reveals unexplored layers of post-transcriptional regulations in groups of RNAs, and is therefore an important step toward a better understanding of the regulatory information conveyed within RNA molecules.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1940-6029
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
714
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
467-79
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Computational prediction of RNA structural motifs involved in post-transcriptional regulatory processes.
pubmed:affiliation
Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehoboth, Rehovot, Israel.
pubmed:publicationType
Journal Article