Author

N. Kishida

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Evolutionary Biology· 1 Microbiology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:host-pathogen & immune response· 2 Organism:virus· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Organism:chicken / avian· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1

Frequent Co-Authors

H. Hasegawa· 3 shared S. Fujisaki· 2 shared S. Watanabe· 2 shared T. Suzuki· 2 shared A. Ainai· 1 shared B. Ermetal· 1 shared D. Akazawa· 1 shared D. E. Wentworth· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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Curved chords = mutual co-authorship

3 shared papersMicrobiology

H. Hasegawa

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Different efficacies of neutralizing antibodies and antiviral drugs on SARS-CoV-2 Omicron subvariants, BA.1 and BA.2

H. Ohashi, T. Hishiki, D. Akazawa, K. S. Kim, J. Woo, K. Shionoya, K. Tsuchimoto, S. Iwanami, S. Moriyama, H. Kinoshita, S. Yamada, Y. Kuroda, T. Yamamoto, N. Kishida, S. Watanabe, , K. Watashi

The paper compares the efficacy of neutralizing antibodies and antiviral drugs against SARS-CoV-2 Omicron subvariants BA.1 and BA.2, finding differential responses to specific treatments.

bioRxiv · Feb 27, 2022Microbiology

The peripheral T cell population is associated with pneumonia severity in cynomolgus monkeys experimentally infected with severe acute respiratory syndrome coronavirus 2

N. Nagata, N. Iwata-Yoshikawa, K. Sano, A. Ainai, N. Shiwa, M. Shirakura, N. Kishida, T. Arita, Y. Suzuki, T. Harada, Y. Kawai, Y. Ami, S. Iida, H. Katano, S. Fujisaki, , H. Hasegawa

This study shows that cynomolgus monkeys with lower peripheral T cell counts experience more severe pneumonia after SARS-CoV-2 infection compared to those with higher T cell counts.

bioRxiv · Jan 7, 2021 · PreprintPathology

Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution

J. Huddleston, J. R. Barnes, T. Rowe, R. Kondor, D. E. Wentworth, L. Whittaker, B. Ermetal, R. S. Daniels, J. W. McCauley, S. Fujisaki, K. Nakamura, N. Kishida, S. Watanabe, H. Hasegawa, I. Barr, , T. Bedford

This study develops a forecasting framework for influenza A/H3N2 evolution by integrating phenotypic antigenic drift data with sequence-based fitness estimates, showing improved long-term predictions.

bioRxiv · Jun 12, 2020Evolutionary Biology