Author

J. Fujii

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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Ecology· 1 Microbiology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:experimental assay· 2 Organism:mouse· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Research Focus:ecology & biodiversity· 1

Frequent Co-Authors

F. Obata· 2 shared R. Ozuru· 2 shared A. Adams· 1 shared A. Belani· 1 shared A. F. Govindarajan· 1 shared A. Kukulya· 1 shared D. Gomez-Ibanez· 1 shared D. R. Yoerger· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersPathology

F. Obata

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Improved biodiversity detection using a large-volume environmental DNA sampler with in situ filtration and implications for marine eDNA sampling strategies

A. F. Govindarajan, L. McCartin, A. Adams, E. Allan, A. Belani, R. Francolini, J. Fujii, D. Gomez-Ibanez, A. Kukulya, F. Marin, K. Tradd, D. R. Yoerger, J. M. McDermott, S. Herrera

This study compares large-volume eDNA sampling with in situ filtration to small-volume conventional sampling, finding that larger samples detect more taxa and are better for deep ocean biodiversity detection.

bioRxiv · Jan 12, 2022Ecology

Stx2 Induces Differential Gene Expression by Activating Several Pathways and Disturbs Circadian Rhythm Genes in the Proximal Tubule.

F. Obata, R. Ozuru, T. Tsuji, T. Matsuba, J. Fujii

This study identifies Stx2-induced differential gene expression and circadian rhythm disruption in proximal tubules, linking these changes to renal dysfunction.

bioRxiv · Jun 11, 2021Pathology

A Machine Learning Model of Microscopic Agglutination Test for Diagnosis of Leptospirosis

Y. Oyamada, R. Ozuru, T. Masuzawa, S. Miyahara, Y. Nikaido, F. Obata, M. Saito, S. Y. A. M. Villanueva, J. Fujii

This paper develops a machine learning model to automate the Microscopic Agglutination Test (MAT) for leptospirosis diagnosis by improving classification accuracy using wavelet coefficient histograms.

bioRxiv · Dec 8, 2020Microbiology