mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein–enriched transcripts

Autor:	Andrew Lee, Min Han, Ye Ding, Dang Long, Molly Hammell, Victor R. Ambros, C. Steven Carmack, Liang Zhang
Rok vydání:	2008
Předmět:	Genetics Messenger RNA biology Immunoprecipitation food and beverages RNA Cell Biology Computational biology biology.organism_classification Biochemistry Transcription (biology) microRNA Gene silencing Molecular Biology Caenorhabditis elegans Biotechnology Ribonucleoprotein
Zdroj:	Nature Methods. 5:813-819
ISSN:	1548-7105 1548-7091
DOI:	10.1038/nmeth.1247
Popis:	Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNA-target interactions. Recently, a dataset of 3,404 miRNA-associated mRNA transcripts was identified by immunoprecipitation of the RNA-induced silencing complex components AIN-1 and AIN-2. Our analysis of this AIN-IP dataset revealed enrichment for defining characteristics of functional miRNA-target interactions, including structural accessibility of target sequences, total free energy of miRNA-target hybridization and topology of base-pairing to the 5' seed region of the miRNA. We used these enriched characteristics as the basis for a quantitative miRNA target prediction method, miRNA targets by weighting immunoprecipitation-enriched parameters (mirWIP), which optimizes sensitivity to verified miRNA-target interactions and specificity to the AIN-IP dataset. MirWIP can be used to capture all known conserved miRNA-mRNA target relationships in Caenorhabditis elegans at a lower false-positive rate than can the current standard methods.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0739c081ac5ea093b31e5cac2140a9a3 https://doi.org/10.1038/nmeth.1247 Zobrazit plný text záznamu Plný text ve formátu PDF