INFLUENZA A SUBTYPING AND HOST ORIGIN CLASSIFICATION USING PROFILE HIDDEN MARKOV MODELS
作者： Fayroz F Sherif , YASSER M KADAH , MAHMOUD EL-HEFNAWI , None
DOI: 10.1142/S021951941240009X
关键词:
摘要: Influenza is one of the most important emerging and reemerging infectious diseases, causing high morbidity mortality in communities (epidemic) worldwide (pandemic). Here, classification human vs. non-human influenza, subtyping influenza viral strains virus done based on profile hidden Markov models (HMM). The classical ways determining subtypes depend mainly antigenic assays, which time-consuming not fully accurate. introduced technique much cheaper faster, yet usually can still yield accuracy. Multiple sequence alignments were for 16 HA 9 NA subtypes, followed by profile-HMMs generation, calibration evaluation using HMMER suite each group. Subtyping accuracy all achieved 100%, while host accuracies around 53% 95.1% according to subtype.
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