Artificial intelligence and Machine Learning based Techniques in Analyzing the COVID-19 Gene Expression data: A Review

The novel Coronavirus associated with respiratory illness has become a new threat to human health as it is spreading very rapidly among the human population. Scientists and healthcare specialists throughout the world are still looking for a breakthrough technology to help combat the Covid-19 outbreak, despite the recent worldwide urgency. The use of Machine Learning (ML) and Artificial Intelligence (AI) in earlier epidemics has encouraged researchers by providing a fresh approach to combating the latest Coronavirus pandemic. This paper aims to comprehensively review the role of AI and ML for analysis of gene expressed data of COVID-1

Research Article A new Informatics Framework for Evaluating the Codon Usage Metrics, Evolutionary Models and Phylogeographic reconstruction of Tomato yellow leaf curl virus (TYLCV) in different regions of Asian countries

Tomato yellow leaf curl virus (TYLCV) is a major devastating viral disease, majorly affecting the tomato production globally. The disease is majorly transmitted by the Whitefly. The Begomovirus (TYLCV) having a six major protein coding genes, among them the C1/AC1 is evidently associated with viral replication. Owing to immense role of C1/AC1 gene, the present study is an initial effort to elucidate the factors shaping the codon usage bias and evolutionary pattern of TYLCV-C1/AC1 gene in five major Asian countries. Based on publically available nucleotide sequence data the Codon usage pattern, Evolutionary and Phylogeographic reconstruction was carried out. The study revealed the presence of significant variation between the codon bias indices in all the selected regions. Implying that the codon usage pattern indices (eNC, CAI, RCDI, GRAVY, Aromo) are seriously affected by selection and mutational pressure, taking a supremacy in shaping the codon usage bias of viral gene. Further, the tMRCA age was 1853, 1939, 1855, 1944, 1828 for China, India, Iran, Oman and South Korea, respectively for TYLCV-C1/AC1 gene. The integrated analysis of Codon usage bias, Evolutionary rate and Phylogeography analysis in viruses signifies the positive role of selection and mutational pressure among the selected regions for TYLCV (C1/AC1) gene

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Not AvailableThe novel Coronavirus associated with respiratory illness has become a new threat to human health as it is spreading very rapidly among the human population. Scientists and healthcare specialists throughout the world are still looking for a breakthrough technology to help combat the Covid-19 outbreak, despite the recent worldwide urgency. The use of Machine Learning (ML) and Artificial Intelligence (AI) in earlier epidemics has encouraged researchers by providing a fresh approach to combating the latest Coronavirus pandemic. This paper aims to comprehensively review the role of AI and ML for analysis of gene expressed data of COVID-19Not Availabl