Integrated analysis of the miRNA-mRNA next-generation sequencing data for finding their associations in different cancer types.

microRNAs (miRNAs) are short, non-coding, endogenous RNA molecule that regulates messenger RNAs (mRNAs) at the post-transcriptional level. The discovery of this regulatory relationship between miRNAs and mRNAs is an important research direction. In this regard, our method proposed an integrated approach to identify the mRNA targets of dysregulated miRNAs using next-generation sequencing data from six cancer types.

In silico markers: an evolutionary and statistical approach to select informative genes of human breast cancer subtypes.

Background: Recent advancement in bioinformatics offers the ability to identify informative genes from high dimensional gene expression data. Selection of informative genes from these large datasets has emerged as an issue of major concern among researchers.

Objective: Gene functionality and regulatory mechanisms can be understood through the analysis of these gene expression data.

Identification of tissue-specific tumor biomarker using different optimization algorithms.

Background: Identification of differentially expressed genes, i.e., genes whose transcript abundance level differs across different biological or physiological conditions, was indeed a challenging task.

Genome-wide analysis of NGS data to compile cancer-specific panels of miRNA biomarkers.

MicroRNAs are small non-coding RNAs that influence gene expression by binding to the 3' UTR of target mRNAs in order to repress protein synthesis. Soon after discovery, microRNA dysregulation has been associated to several pathologies. In particular, they have often been reported as differentially expressed in healthy and tumor samples.

Binding Activity Prediction of Cyclin-Dependent Inhibitors.

The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust estimation of ligand binding activity has been a challenging task in drug design.