Human gene sequences are considered a primary source of comprehensive information
about different body conditions. A wide variety of diseases including cancer, heart issues …

Background: Systems biology and network modeling represent, nowadays, the hallmark
approaches for the development of predictive and targeted-treatment based precision …

Recently, in most existing studies, it is assumed that there are no interaction relationships
between drugs and targets with unknown interactions. However, unknown interactions mean …

Purpose This paper has used the well-known machine learning (ML) computational
algorithm with Internet of Things (IoT) devices to predict the COVID-19 disease and to …

The problem of disease prediction and recommendation has been well studied. There exist
several techniques for disease prediction but suffer to achieve the expected performance …

Transcription profiling is a key process that can reveal those biological mechanisms driving
the response to various exposure conditions or gene perturbations. In this work, we …

Motivation: In vitro experiment-based drug-target interaction (DTI) exploration demands
more human, financial and data resources. In silico approaches have been recommended …

Nowadays, with the rapid development of intelligent technology, it is urgent to effectively
prevent infectious diseases and ensure people's privacy. The present work constructs the …

The prediction of gene mutation of bacteria when exposed to different conditions is
beneficial in the development of drugs and vaccines. However, the existing prediction …

Machine learning algorithms (MLAs) have recently been applied to predict gene mutations
of Escherichia coli (E. coli) under different exposure conditions, with room for improvement …