STarMir: a web server for prediction of microRNA binding sites
نویسندگان
چکیده
STarMir web server predicts microRNA (miRNA) binding sites on a target ribonucleic acid (RNA). STarMir is an implementation of logistic prediction models developed with miRNA binding data from crosslinking immunoprecipitation (CLIP) studies (Liu,C., Mallick, B., Long, D., Rennie, W.A., Wolenc, A., Carmack, C.S. and Ding, Y. (2013). CLIP-based prediction of mammalian microRNA binding sites. Nucleic Acids Res., 41(14), e138). In both intra-dataset and inter-dataset validations, the models showed major improvements over established algorithms in predictions of both seed and seedless sites. General applicability of the models was indicated by good performance in cross-species validations. The input data for STarMir is processed by the web server to perform prediction of miRNA binding sites, compute comprehensive sequence, thermodynamic and target structure features and a logistic probability as a measure of confidence for each predicted site. For each of seed and seedless sites and for all three regions of a mRNA (3' UTR, CDS and 5' UTR), STarMir output includes the computed binding site features, the logistic probability and a publication-quality diagram of the predicted miRNA:target hybrid. The prediction results are available through both an interactive viewer and downloadable text files. As an application module of the Sfold RNA package (http://sfold.wadsworth.org), STarMir is freely available to all at http://sfold.wadsworth.org/starmir.html.
منابع مشابه
Study of PKA binding sites in cAMP-signaling pathway using structural protein-protein interaction networks
Backgroud: Protein-protein interaction, plays a key role in signal transduction in signaling pathways. Different approaches are used for prediction of these interactions including experimental and computational approaches. In conventional node-edge protein-protein interaction networks, we can only see which proteins interact but ‘structural networks’ show us how these proteins inter...
متن کاملProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites
The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites t...
متن کاملTAPIR, a web server for the prediction of plant microRNA targets, including target mimics
UNLABELLED We present a new web server called TAPIR, designed for the prediction of plant microRNA targets. The server offers the possibility to search for plant miRNA targets using a fast and a precise algorithm. The precise option is much slower but guarantees to find less perfectly paired miRNA-target duplexes. Furthermore, the precise option allows the prediction of target mimics, which are...
متن کاملBioinformatics prediction and experimental validation of VH antibody fragment interacting with Neisseria meningitidis factor H binding protein
Objective(s): We previously conducted an in silico research on the interactions between the ribosome display-selected single chain variable fragment (scFv) and factor H binding protein (fHbp) of Neisseria meningitidis. We found that heavy chain variable (VH) fragment of this scFv had considerable affinity to fHbp. These results led us to evaluate the ability of this sm...
متن کاملPredictRegulon: a web server for the prediction of the regulatory protein binding sites and operons in prokaryote genomes
An interactive web server is developed for predicting the potential binding sites and its target operons for a given regulatory protein in prokaryotic genomes. The program allows users to submit known or experimentally determined binding sites of a regulatory protein as ungapped multiple sequence alignments. It analyses the upstream regions of all genes in a user-selected prokaryote genome and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 42 شماره
صفحات -
تاریخ انتشار 2014