Author

Haruyuki Kataguchi

Institutions: Toyama University Hospital, University of Toyama

Observed institutions: Toyama University Hospital, University of Toyama

ORCID: 0000-0001-9210-9924

Observed ORCID: 0000-0001-9210-9924

OpenAlex ID: A5086548281

Prediction of infectivity of SARS-CoV2: Mathematical model with analysis of docking simulation for spike proteins and angiotensin-converting enzyme 2

2022 · Yutaka Takaoka, Aki Sugano, et al. · Microbial Risk Analysis · 8

SARS-CoV-2 Omicron BA.2.75 Variant May Be Much More Infective than Preexisting Variants Based on In Silico Model

2022 · Aki Sugano, Yutaka Takaoka, et al. · Microorganisms · 7

SARS-CoV-2 Omicron XBB.1.5 May Be a Variant That Spreads More Widely and Faster Than Other Variants

2023 · Aki Sugano, Haruyuki Kataguchi, et al. · bioRxiv (Cold Spring Harbor Laboratory) · 6

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

2023 · Aki Sugano, Junon Murakami, et al. · Microbial Risk Analysis · 3

Works count: 4

Citation count: 24

H-index: 3

I10-index: