A novel approach for protein secondary structure prediction using encoder-decoder with attention mechanism model.

Computational biology faces many challenges like protein secondary structure prediction (PSS), prediction of solvent accessibility, etc. In this work, we addressed PSS prediction. PSS is based on sequence-structure mapping and interaction among amino acid residues.

Comparison of academic performance of medical undergraduate students between routine class room teaching and online assisted teaching in biochemistry during COVID pandemic.

The new curriculum of competency based medical education (CBME) implemented for phase1 medical undergraduates could not go on to completion due to the sudden outbreak of the COVID-19 pandemic. The educational institutions therefore resorted to online teaching modalities over conventional class room teachings. Hence this study aimed to compare the academic performance of students between routine classroom teaching and online assisted teaching with assignments.

A survey on gene expression data analysis using deep learning methods for cancer diagnosis.

Gene Expression Data is the biological data to extract meaningful hidden information from the gene dataset. This gene information is used for disease diagnosis especially in cancer treatment based on the variations in gene expression levels. DNA microarray is an efficient method for gene expression classification and prediction of cancer disease for specific types of cancer.

Phenotypic and transcriptomic changes in zebrafish (Danio rerio) embryos/larvae following cypermethrin exposure.

Cypermethrin is one of the widely used type-II pyrethroid and the indiscriminate use of this pesticide leads to life threatening effects and in particular showed developmental effects in sensitive populations such as children and pregnant woman. However, the molecular mechanisms underlying cypermethrin-induced development toxicity is not well defined. To address this gap, the present study was designed to investigate the phenotypic and transcriptomic (next generation RNA-Seq method) impact of cypermethrin in zebrafish embryos as a model system.

Investigation of machine learning techniques on proteomics: A comprehensive survey.

Proteomics is the extensive investigation of proteins which has empowered the recognizable proof of consistently expanding quantities of protein. Proteins are necessary part of living life form, with numerous capacities. The proteome is the complete arrangement of proteins that are created or altered by a life form or framework of the organism.

Cuckoo search optimisation for feature selection in cancer classification: a new approach.

Cuckoo Search (CS) optimisation algorithm is used for feature selection in cancer classification using microarray gene expression data. Since the gene expression data has thousands of genes and a small number of samples, feature selection methods can be used for the selection of informative genes to improve the classification accuracy. Initially, the genes are ranked based on T-statistics, Signal-to-Noise Ratio (SNR) and F-statistics values.

A comparative analysis of swarm intelligence techniques for feature selection in cancer classification.

Feature selection in cancer classification is a central area of research in the field of bioinformatics and used to select the informative genes from thousands of genes of the microarray. The genes are ranked based on T-statistics, signal-to-noise ratio (SNR), and F-test values. The swarm intelligence (SI) technique finds the informative genes from the top-m ranked genes.

Lung cancer classification using neural networks for CT images.

Early detection of cancer is the most promising way to enhance a patient's chance for survival. This paper presents a computer aided classification method in computed tomography (CT) images of lungs developed using artificial neural network. The entire lung is segmented from the CT images and the parameters are calculated from the segmented image.

Efficacy of zinc in the treatment of severe pneumonia in hospitalized children <2 y old.

Background: Severe pneumonia remains a leading cause of morbidity and mortality in undernourished young children in developing countries.

Objective: This study evaluated the effect of adjuvant zinc therapy on recovery from severe pneumonia by hospitalized children in southern India who were receiving standard antibiotic therapy.

Design: This randomized, double-blind, placebo-controlled clinical trial was conducted at the Christian Medical College Hospital, an 1800-bed teaching hospital in Tamilnadu, India.