Prioritizing severity level of COVID-19 using correlation coefficient and intuitionistic fuzzy logic.

During the peak of COVID-19 pandemic crisis in 2020 and 2021, with limited medical resources and surge in Covid cases in every hospital and clinic, identifying the most vulnerable patient requiring immediate critical treatment was a great challenge for the medical practitioners. And if such a patient suffers from multiple ailments, his/her condition may deteriorate rapidly if proper treatment is delayed any further. In this paper, we used a novel method which supports medical care units in identifying the patients who need urgent medical treatment.

iSignDB: A database for smartphone signature biometrics.

The signature has long been in use for the user verification. These signatures have user specific features that differentiate the individual for authentication. The signature verification can be offline or online.

A bacterial phyla dataset for protein function prediction.

Protein function prediction has been the most worked upon and the most challenging problem for computational biologists. The vast majority of known proteins have yet not been characterised experimentally, and there is significant gap between their structures and functions. New un-annotated sequences are being added to the public protein databases (e.

A deep learning ensemble for function prediction of hypothetical proteins from pathogenic bacterial species.

Protein function prediction is a crucial task in the post-genomics era due to their diverse irreplaceable roles in a biological system. Traditional methods involved cost-intensive and time-consuming molecular biology techniques but they proved to be ineffective after the outburst of sequencing data through the advent of cost-effective and advanced sequencing techniques. To manage the pace of annotation with that of data generation, there is a shift to computational approaches which are based on homology, sequence and structure-based features, protein-protein interaction networks, phylogenetic profiles, and physicochemical properties, etc.

Sequence based prediction of enhancer regions from DNA random walk.

Regulatory elements play a critical role in development process of eukaryotic organisms by controlling the spatio-temporal pattern of gene expression. Enhancer is one of these elements which contributes to the regulation of gene expression through chromatin loop or eRNA expression. Experimental identification of a novel enhancer is a costly exercise, due to which there is an interest in computational approaches to predict enhancer regions in a genome.