Fast and accurate machine learning based approach to detect inter kingdom horizontally transferred genes in Eukaryotes

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	Fast and accurate machine learning based approach to detect inter kingdom horizontally transferred genes in Eukaryotes
	Parsania, C.; Li, A.; Ho, J.; Wong, K. H.
	2018-07-06
Source Publication	Intelligent Systems for Molecular Biology
Abstract	Horizontal gene transfer (HGT) has been much less studied in Eukaryotes in contrast to Prokaryotes; while partly because HGT is relatively less frequent in Eukaryotes, but mainly due to the fact that means and tools for systematic and easy identification of horizontally transferred (HT) genes in Eukaryotes were not available until recently. In this study, we developed a machine learning based method to detect inter kingdom HT genes. We used quantitative measures derived from the outcome of basic local alignment search tool for protein (BLAST-P) performed against non-redundant (nr) protein database. Our model shows 91% true positive rate and 0 % false positive rate for the test data derived from phylogenetically validated HT genes. As a pilot project, we focus on the fungi kingdom, in which many species often shared natural habitat with other species and thus providing opportunities for HGT to occur. In total, we have identified 838 HT genes from six fungal genomes so far and the data are deposited in a database. Our program will be extended to other Eukaryotes, and the results will serve as a platform for cross species HGT studies and tracing evolutionary marks in multiple domains of life.
Keyword	machine learning inter kingdom horizontally transferred genes Eukaryotes
Language	英語English
The Source to Article	PB_Publication
PUB ID	40069
Document Type	Conference paper
Collection	DEPARTMENT OF BIOMEDICAL SCIENCES Faculty of Health Sciences
Corresponding Author	Ho, J.; Wong, K. H.
Recommended Citation GB/T 7714	Parsania, C.,Li, A.,Ho, J.,et al. Fast and accurate machine learning based approach to detect inter kingdom horizontally transferred genes in Eukaryotes[C], 2018.
APA	Parsania, C.., Li, A.., Ho, J.., & Wong, K. H. (2018). Fast and accurate machine learning based approach to detect inter kingdom horizontally transferred genes in Eukaryotes. Intelligent Systems for Molecular Biology.

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