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分子標的薬アファチニブの薬効予測を実現するシミュレーション解析と数理モデル
Sugano, Aki
(Principal Investigator)
Takaoka, Yutaka
(Co-Investigator(Kenkyū-buntansha))
Ota, Mika
(Co-Investigator(Kenkyū-buntansha))
医薬AI・データ科学講座
Data Science Center for Medicine and Hospital Management
Overview
Research output
(2)
Research output
Research output per year
2022
2022
2023
2023
2
Article
Research output per year
Research output per year
2 results
Publication Year, Title
(descending)
Publication Year, Title
(ascending)
Title
Type
Search results
2023
In silico binding affinity of the spike protein with ACE2 and the relative evolutionary distance of S gene may be potential factors rapidly obtained for the initial risk of SARS-CoV-2
Sugano, A.
, Murakami, J., Kataguchi, H.,
Ohta, M.
,
Someya, Y.
, Kimura, S.,
Kanno, A.
, Maniwa, Y.,
Tabata, T.
,
Tobe, K.
&
Takaoka, Y.
,
2023/12
,
In:
Microbial Risk Analysis.
25
, 100278.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
COVID-19
100%
Binding Affinity
100%
Spike Protein
100%
Evolutionary Distance
100%
Spike Protein Gene
100%
2
Scopus citations
2022
SARS-CoV-2 Omicron BA.2.75 Variant May Be Much More Infective than Preexisting Variants Based on In Silico Model
Sugano, A.
,
Takaoka, Y.
, Kataguchi, H.,
Ohta, M.
, Kimura, S., Araki, M.,
Morinaga, Y.
&
Yamamoto, Y.
,
2022/10
,
In:
Microorganisms.
10
,
10
, 2090.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
In Silico Modeling
100%
SARS-CoV-2 Omicron
100%
BA.2.75
100%
Spike
100%
SARS Coronavirus
100%
3
Scopus citations