Web Based

Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regulatory connectivity between miRNAs and TFs. Here we investigate the connectivity from TFs and miRNAs to other genes and each other using text mining, TF promoter binding site and 6 different miRNA binding site prediction methods.

The non-coding elements of a genome, with many of them considered as junk earlier, have now started gaining long due respectability, with microRNAs as the best current example. MicroRNAs bind preferentially to the 3' untranslated regions 9UTRs) of the target genes and negatively regulate their expression most of the time. Several microRNA: target prediction softwares have been developed based upon various assumptions and the majority of them consider the free energy of binding of a target to its microRNA and seed conservation.

MicroRNAs (miRNAs) are small non-coding nucleotide sequences between 17 and 25 nucleotides in length that primarily function in the regulation of gene expression. A since miRNA has thousand of predict targets in a complex, regulatory cell signaling network. Therefore, it is of interest to study multiple target genes simultaneously. Hence, we describe a web tool (developed using Java programming language and MySQL database server) to analyse multiple targets of pre-selected miRNAs.

Long non-coding RNAs (lncRNAs) represent a class of potent regulators of gene expression that are found in a wide array of eukaryotes; however, our knowledge about these molecules in plants is still very limited. In particular, a number of model plant species still lack comprehensive data sets of lncRNAs and their annotations, and very little is known about their biological roles. To meet these shortcomings, we created an online database of lncRNAs in 10 model plant species.