首页|Machine learning models can identify individuals based on a resident oral bacter iophage family
Machine learning models can identify individuals based on a resident oral bacter iophage family
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: “Metagenomic studies have revolutionized the study of novel phages. “However these studies trade depth of coverage for breadth. “We show that the targeted sequencing of a small region of a phage terminase fam ily can provide sufficient sequence diversity to serve as an individual-specific barcode or a phageprint, defined as the relative abundance profile of the varia nts within a terminase family. By collecting 700 oral samples from 100 individ uals living on multiple continents, we found a consistent trend wherein each ind ividual harbors one or two dominant variants that coexist with numerous low-abun dance variants. By tracking phageprints over the span of a month across ten indi viduals, we observed that phageprints were generally stable, and found instances of concordant temporal fluctuations of variants shared between partners.
BacteriophagesBioinformaticsBiotechn ologyBiotechnology - BioinformaticsCyborgsEmerging TechnologiesEnzymes a nd CoenzymesInformation TechnologyMachine LearningTerminaseViruses
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