Novel machine learning method allerStat identifies statistically significant allergen-specific patterns in protein sequences.

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第一作者： Kento,Goto

第一单位： Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi, Japan.

作者： Kento,Goto ^[1] ; Norimasa,Tamehiro ^[2] ; Takumi,Yoshida ^[1] ; Hiroyuki,Hanada ^[3] ; Takuto,Sakuma ^[1] ; Reiko,Adachi ^[2] ; Kazunari,Kondo ^[4] ; Ichiro,Takeuchi ^[5]

作者单位： Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi, Japan. ^[1] Division of Biochemistry, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan. ^[2] Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan. ^[3] Division of Biochemistry, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan. Electronic address: kondo@nihs.go.jp. ^[4] Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan; Graduate School of Engineering, Nagoya University, Furo-cho, Nagoya, Japan. Electronic address: ichiro.takeuchi@mae.nagoya-u.ac.jp. ^[5]

关键词 allergen amino acid computational biology immunoglobulin E major histocompatibility complex mathematical modeling protein motif statistics

主题词变应原(Allergens);氨基酸序列(Amino Acid Sequence);蛋白质类(Proteins)

DOI 10.1016/j.jbc.2023.104733

PMID 37086787

发布时间 2023-07-06

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