Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method

10.1038/s41598-017-01699-z

Saved in:

Bibliographic Details
Main Authors:	Yao, Y, Li, X, Liao, B, Huang, L, He, P, Wang, F, Yang, J, Sun, H, Zhao, Y
Other Authors:	CENTRE FOR MARITIME STUDIES
Format:	Article
Published:	Nature Publishing Group 2020
Subjects:	Influenza virus hemagglutinin virus antigen algorithm amino acid sequence amino acid substitution chemistry genetics human immunology Influenza A virus (H3N2) molecular evolution mutation Algorithms Amino Acid Sequence Amino Acid Substitution Antigens, Viral Evolution, Molecular Hemagglutinin Glycoproteins, Influenza Virus Humans Influenza A Virus, H3N2 Subtype Mutation
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/178615
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore

id	sg-nus-scholar.10635-178615
record_format	dspace
spelling	sg-nus-scholar.10635-1786152024-11-12T12:16:20Z Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method Yao, Y Li, X Liao, B Huang, L He, P Wang, F Yang, J Sun, H Zhao, Y Yang, J CENTRE FOR MARITIME STUDIES Influenza virus hemagglutinin virus antigen algorithm amino acid sequence amino acid substitution chemistry genetics human immunology Influenza A virus (H3N2) molecular evolution mutation Algorithms Amino Acid Sequence Amino Acid Substitution Antigens, Viral Evolution, Molecular Hemagglutinin Glycoproteins, Influenza Virus Humans Influenza A Virus, H3N2 Subtype Mutation 10.1038/s41598-017-01699-z Scientific Reports 7 1 1545 2020-10-20T10:33:15Z 2020-10-20T10:33:15Z 2017 Article Yao, Y, Li, X, Liao, B, Huang, L, He, P, Wang, F, Yang, J, Sun, H, Zhao, Y, Yang, J (2017). Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method. Scientific Reports 7 (1) : 1545. ScholarBank@NUS Repository. https://doi.org/10.1038/s41598-017-01699-z 2045-2322 https://scholarbank.nus.edu.sg/handle/10635/178615 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Nature Publishing Group Unpaywall 20201031
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Influenza virus hemagglutinin virus antigen algorithm amino acid sequence amino acid substitution chemistry genetics human immunology Influenza A virus (H3N2) molecular evolution mutation Algorithms Amino Acid Sequence Amino Acid Substitution Antigens, Viral Evolution, Molecular Hemagglutinin Glycoproteins, Influenza Virus Humans Influenza A Virus, H3N2 Subtype Mutation
spellingShingle	Influenza virus hemagglutinin virus antigen algorithm amino acid sequence amino acid substitution chemistry genetics human immunology Influenza A virus (H3N2) molecular evolution mutation Algorithms Amino Acid Sequence Amino Acid Substitution Antigens, Viral Evolution, Molecular Hemagglutinin Glycoproteins, Influenza Virus Humans Influenza A Virus, H3N2 Subtype Mutation Yao, Y Li, X Liao, B Huang, L He, P Wang, F Yang, J Sun, H Zhao, Y Yang, J Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method
description	10.1038/s41598-017-01699-z
author2	CENTRE FOR MARITIME STUDIES
author_facet	CENTRE FOR MARITIME STUDIES Yao, Y Li, X Liao, B Huang, L He, P Wang, F Yang, J Sun, H Zhao, Y Yang, J
format	Article
author	Yao, Y Li, X Liao, B Huang, L He, P Wang, F Yang, J Sun, H Zhao, Y Yang, J
author_sort	Yao, Y
title	Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method
title_short	Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method
title_full	Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method
title_fullStr	Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method
title_full_unstemmed	Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method
title_sort	predicting influenza antigenicity from hemagglutintin sequence data based on a joint random forest method
publisher	Nature Publishing Group
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/178615
_version_	1821222330440876032

Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method

Similar Items