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We describe miTRATA, the first web-based tool for microRNA Truncation and Tailing Analysis--the analysis of 3' modifications of microRNAs including the loss or gain of nucleotides relative to the canonical sequence. miTRATA is implemented in Python (version 3) and employs parallel processing modules to enhance its scalability when analyzing multiple small RNA (sRNA) sequencing datasets. It utilizes miRBase, currently version 21, as a source of known microRNAs for analysis. miTRATA notifies user(s) via email to download as well as visualize the results online.

Protein-protein interactions (PPIs) and microRNA (miRNA)-target interactions are important for deciphering the mechanisms of tumorigenesis. However, current PPI databases do not support cancer-specific analysis. Also, no available databases can be used to retrieve cancer-associated miRNA-target interactions. As the pathogenesis of human cancers is affected by several miRNAs rather than a single miRNA, it is needed to uncover miRNA synergism in a systems level.

Endometrial cancer (EC) is the most frequently diagnosed gynecological malignancy and the fourth most common cancer diagnosis overall among women. As with many other forms of cancer, it has been shown that certain miRNAs are differentially expressed in EC and these miRNAs are believed to play important roles as regulators of processes involved in the development of the disease.

Transposable elements (TEs) comprise a major fraction of many plant genomes and are known to drive their organization and evolution. Several studies show that these repetitive elements have a prominent role in shaping noncoding regions of the genome such as microRNA (miRNA) loci, which are components of post-transcriptional regulation mechanisms.

MicroRNAs play important roles in most biological processes, including cell proliferation, tissue differentiation, and embryonic development, among others. They originate from precursor transcripts (pre-miRNAs), which contain phylogenetically conserved stem-loop structures. An important bioinformatics problem is to distinguish the pre-miRNAs from pseudo pre-miRNAs that have similar stem-loop structures. We present here a novel method for tackling this bioinformatics problem.

A large number of studies have suggested extracellular microRNAs (microRNAs in biofluids) as potential noninvasive biomarkers for pathophysiological conditions such as cancer. However, reported differentially expressed signatures of extracellular miRNAs in diseases are not uniformly consistent among studies. Here, we present "ExcellmiRDB", a curated online database that provides integrated information about miRNAs levels in biofluids in a user-friendly way.