Author

Katsufumi Sato

Atmosphere and Ocean Research Institute, The University of TokyoORCID 0000-0002-7557-4784Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 1 Zoology· 1

Signature Assays, Organisms & Methods

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Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Research Focus:metabolism & bioenergetics· 1 Assay:metabolomics· 1 Organism:mouse· 1

Frequent Co-Authors

Akiko Yamazoe-Umemoto· 1 shared Akinori TakahashiiD· 1 shared Azusa KamikouchiiD· 1 shared Daiki Inamori· 1 shared Daisuke Takaichi· 1 shared Fumie HiramatsuiD· 1 shared Ippei SuzukiiD· 1 shared Kagari AokiiD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperNeuroscience

Akiko Yamazoe-Umemoto

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2 papers

Recent·Most cited

ZoologybioRxivPreprintJan 22, 2025

Allometric studies on human- and pig-sized Delphinidae to understand resting metabolic rates with respiratory measurements

Ippei Suzuki, Yasuaki Niizuma, Daiki Inamori…·Kagari Aoki

This study measures resting metabolic rates in dolphins and compares them to terrestrial mammals, finding a different allometric scaling relationship in aquatic species.

DOI 10.1101/2025.01.22.633296

metabolomicsstatistical model

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NeuroscienceFrontiers in NeurosciencePeer-reviewedJun 28, 2019

A hybrid versatile method for state estimation and feature extraction from the trajectory of animal behavior

Shuhei J. Yamazaki, Kazuya Ohara, Kentaro Ito…·Koutarou D. Kimura

This paper introduces a hybrid machine learning method to estimate behavioral states and extract features from low-content animal trajectory data, validated across diverse species and environments.

13 citations

humanmouse

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