Identifies the binding sites of RNA molecules. RBind transforms the RNA tertiary into a network, where nucleotides are nodes, and their non-covalent interactions with each other are the edges. It recognizes binding sites by determining the degree values for short-range binding cavity and closeness values for long-range allosteric effect. This tool is useful to find critical nucleotides for binding.
Explores lncRNA–RNA interactions by finding the minimum free energy joint structure of two RNA molecules based on base pairing. LncTar overwhelms the existing RNA–RNA prediction tools on the following aspects: (i) LncTar does not have a limit to RNA size and can process all length of current RNA molecules; (ii) this tool provides a quantitative standard to automatically determine whether two RNA molecules interact with each other. LncTar takes account of multiple binding sites using a matching algorithm, which finds the region of the minimum free energy joint structure between the input RNA sequences.
A graphical web tool to compute and visualize putative miRNA response elements in long non-coding RNAs (lncRNAs), along with different measures to assess their likely behavior as competitive endogenous RNAs. The algorithm is based on sequence complementarity and allows users to fix parameters to allow flexible search. The possibility of adding expression data to the prediction representation in the web tool, greatly facilitates downstream functional analysis. spongeScan differs from other lncRNA–miRNA interactions prediction sites that utilize CLIP-seq data in allowing massive searchers on user provided data and in being available for any organism with sequence information.
Predicts the potential long non-coding RNA (lncRNA-protein) associations. LPI-NRLMF is a matrix factorization computational approach for uncovering lncRNA-protein relationships. This method adopts a semi-supervised learning strategy, which deduces unknown data mainly by known interactions and their similarities, so negative samples are not needed. It was assessed by performing a cross validation of known experimental lncRNA-protein scores.
Identifies long non-coding RNAs (lncRNAs)-associated modules from protein interaction networks and predicts the function of lncRNAs based on the protein functions in the modules. Lncin utilizes not only the lncRNA-mRNA co-expression networks based on the rank of correlation which is a better measure of similarity than the correlation value, but also protein-protein interactions among co-expressed mRNAs to identify a set of mRNAs that may be modulated by lncRNA.
Serves for long non-coding RNAs (lncRNA) target prediction based on nucleic acid thermodynamics. lncRNATargets is a web application that determines RNA targets in high throughput. It assists users to find potential lncRNA-messenger RNA (mRNA) target relations that may unveil the mechanism of lncRNAs. It provides colored result displays that allows users to better understand the prediction.
Predicts long non-coding RNAs (lncRNA) mechanisms by using both RNA-RNA and RNA-protein interaction. MEchRNA is a standalone software that starts from lncRNA-target interactions forecasting and then determines RNA-binding protein (RBP) binding sites. Afterwards, it finds correlation between the lncRNA and targets and produces candidate mechanisms which are filtered to retain only those that best explain the observed data.