Abstract
Horizontal gene transfer (HGT) takes place when two organisms share their genetic material. Contrary to the ancestral transfer of genes, viz. Vertical gene transfer, the HGT, is very commonly found in many species of bacteria even if there is distantly related evidence which is phylogenies, sequence comparison, and genome characteristics. In this work, we use an Artificial Intelligence/Machine Learning (AI/ML) model which is based on unsupervised learning on the human fungal pathogenesis dataset. The AI/ML model discovers distinctive classification/annotation features which are able to predict a correlation between pathogenesis and horizontal transfer events with unknown queries. A brief perspective of this is enlisted in our chapter.
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MB and GD contributed equally. PS ideated the project and proposed the horigene concept. All other authors contributed to the general framework of the chapter and agreed to the sections of the manuscript before PS proofreading it.
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Github link: goutamdh/HGT_Website_Server (github.com).
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Bhushan, M. et al. (2023). Challenges in Eventing Horizontal Gene Transfer. In: Mani, I., Singh, V., Alzahrani, K.J., Chu, DT. (eds) Microbial Genomic Islands in Adaptation and Pathogenicity. Springer, Singapore. https://doi.org/10.1007/978-981-19-9342-8_16
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DOI: https://doi.org/10.1007/978-981-19-9342-8_16
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