首页|Ghent University Reports Findings in Klebsiella (Prediction of Klebsiella phage- host specificity at the strain level)
Ghent University Reports Findings in Klebsiella (Prediction of Klebsiella phage- host specificity at the strain level)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Gram-Negative Bacteria - Klebsiella is the subject of a report. According to news originating from Ghe nt, Belgium, by NewsRx correspondents, research stated, “Phages are increasingly considered promising alternatives to target drug-resistant bacterial pathogens. However, their often-narrow host range can make it challenging to find matching phages against bacteria of interest.” Our news journalists obtained a quote from the research from Ghent University, “ Current computational tools do not accurately predict interactions at the strain level in a way that is relevant and properly evaluated for practical use. We pr esent PhageHostLearn, a machine learning system that predicts strain-level inter actions between receptor-binding proteins and bacterial receptors for Klebsiella phage-bacteria pairs. We evaluate this system both in silico and in the laborat ory, in the clinically relevant setting of finding matching phages against bacte rial strains. PhageHostLearn reaches a cross-validated ROC AUC of up to 81.8% in silico and maintains this performance in laboratory validation.”
GhentBelgiumEuropeCyborgsEmergin g TechnologiesEnterobacteriaceaeGammaproteobacteriaGram-Negative BacteriaGram-Negative Facultatively Anaerobic RodsKlebsiellaMachine LearningProte obacteria
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