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دسته بندی:
یادگیری ماشین - machine learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Conservation region finding for influenza A viruses by machine learning methods of N-linked glycosylation sites and B-cell epitopes
ترجمه فارسی عنوان مقاله:
یافتن منطقه حفاظت از ویروس های آنفلوانزا A با استفاده از روش های یادگیری ماشینی سایت های گلیکوزیلاسیون مرتبط با N و اپی توپ های سلول B
منبع:
Sciencedirect - Elsevier - Mathematical Biosciences, 315 (2019) 108217: doi:10:1016/j:mbs:2019:108217
نویسنده:
Jone-Han Liua, Chi-Chang Changb,c, Chi-Wei Chend, Li-Ting Wongd, Yen-Wei Chud,e,⁎
چکیده انگلیسی:
Influenza type A, a serious infectious disease of the human respiratory tract, poses an enormous threat to
human health worldwide. It leads to high mortality rates in poultry, pigs, and humans. The primary target
identity regions for the human immune system are hemagglutinin (HA) and neuraminidase (NA), two surface
proteins of the influenza A virus. Research and development of vaccines is highly complex because the influenza
A virus evolves rapidly. This study focused on three genetic features of viral surface proteins: ribonucleic
acid (RNA) sequence conservation, linear B-cell epitopes, and N-linked glycosylation. On the basis of
these three properties, we analyzed 12,832 HA and 9487 NA protein sequences, which we retrieved from the
influenza virus database. We classified the viral surface protein sequences into the 18 HA and 11 NA subtypes
that have been identified thus far. Using available analytic tools, we searched for the representative strain of
each virus subtype. Furthermore, using machine learning methods, we looked for conservation regions with
sequences showing linear B-cell epitopes and N-linked glycosylation. Compared to the prediction of the
Immune Epitope Database (IEDB) antibody neutralization response (i.e., screening of antibody sequence regions),
in this study, the virus sequence coverage was large and accurate and contained N-linked glycosylation
sites. The results of this study proved that we can use the machine learning-based prediction method to solve
the problem of vaccine invalidation that occurred during the rapid evolution of the influenza A virus and also
as a prevaccine assessment. In addition, the screening fragments can be used as a universal influenza vaccine
design reference in the future.
Keywords: Hemagglutinin | Neuraminidase | N-linked glycosylation | Linear B-cell epitope | Machine learning
قیمت: رایگان
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