Publications

šŸ“š Peer-reviewed Papers

2026

  • Disentanglement of batch effects and biological signals across conditions in the single-cell transcriptome
    Shunta Sakaguchi#, Masato Tsutsumi# (co-first), Kentaro Nishi, Naoki Honda
    Patterns (in press; expected October 2026) DOI
  • Artificial-Intelligence-Based Cephalometric Landmark Detection in Lateral Cephalograms
    Manami Yamaguchi, Masato Tsutsumi, Yasuhiro Kuroda, Yoshiki Soeda, Tetsutaro Yamaguchi
    Journal of Clinical Medicine (July 30, 2026) PDF | DOI

2024

  • Deciphering the origin of developmental stability: The role of intracellular expression variability in evolutionary conservation
    Yui Uchida, Masato Tsutsumi, Shunsuke Ichii, Naoki Irie, Chikara Furusawa
    Evolution & Development (March 2024) PDF | Code

2023

  • A deep learning approach for morphological feature extraction based on variational auto-encoder: an application to mandible shape
    Masato Tsutsumi, Nen Saito, Daisuke Koyabu, Chikara Furusawa
    npj Systems Biology and Applications (July 6, 2023) PDF | Code

šŸ“ƒ Preprints

2026

  • Mind the gap: quantifying population–individual gap in depressive symptom dynamics through energy landscapes
    Masato Tsutsumi, Taisei Kubo, Takahiro A. Kato, Naoki Honda
    bioRxiv (May 24, 2026; v2) PDF | DOI
  • Chemosensory input suppresses cannibalism by stabilizing social feeding boundaries in Drosophila larvae
    Nagisa Matsuda-Watanabe, Masato Tsutsumi, Misako Okumura, Takahiro Chihara
    In submission
  • Decoding Anadara shell morphology with deep learning
    Masato Tsutsumi, Nen Saito, Tomohiro Yamaguchi, Takenori Sasaki, Chikara Furusawa
    bioRxiv (April 21, 2026) PDF | DOI

šŸŽ¤ Invited Talks

2026

  • AI for measuring morphological differences among living organisms
    Masato Tsutsumi
    FY2026 University of Tsukuba Open Lecture: Frontiers of Interdisciplinary Life Science Research 2026 (July 30, 2026) Invited
  • Towards quantification of form using information science
    Masato Tsutsumi
    Workshop on Quantification of Form 2026 (July 27, 2026) Invited
  • Development of methods for quantifying biological morphology with an information-science approach
    Masato Tsutsumi
    78th Annual Meeting of the Japan Society for Cell Biology (July 15, 2026) Invited
  • Variational energy landscape analysis reveals population trends and individual heterogeneity during and after COVID-19 emergency declarations
    Masato Tsutsumi
    40th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2026) (June 9, 2026) Invited
  • Towards quantification of diverse life phenomena: morphology, behavior, and psychology as information
    Masato Tsutsumi
    SSTB2026 - Spring School for Theoretical Biology 2026- (March 5, 2026) Invited

2024

  • Development of quantitative analysis methods for biological morphology using deep learning
    Japan Society for Industrial and Applied Mathematics Annual Meeting 2024 (September 16, 2024)
  • Development of quantitative analysis methods for biological morphology using deep learning
    Online Seminar Series “Future of Evolutionary Biology with AI” (March 9, 2024)
  • Development of quantitative analysis methods for biological morphology using deep learning
    8th Theoretical Immunology Workshop (February 14, 2024)

2022

  • Quantification of various biological morphologies using machine learning
    Hiroshima University Mathematical Life Sciences Program Seminar (November 10, 2022)

2021

  • Quantification and application of biological morphology using machine learning: Focusing on primate mandibles
    National Institute for Basic Biology Departmental Seminar (October 2021)

šŸ—£ļø Conference Presentations

2026

  • Mind the gap: quantifying population–individual differences in depressive symptom dynamics using energy landscapes
    2nd Systems Behavioral Science Workshop (July 12, 2026)
  • Morphological character selection using machine learning for phylogenetic analysis: revisiting the phylogenetic position of lepidosaurs
    Annual Meeting of the Palaeontological Society of Japan 2026 (June 27, 2026)
  • Quantitative Analysis of Biological Morphology and Behavior Based on Deep Learning: Development of Morpho-VAE and DOLO
    Frontiers of coevolutionary phenotypic emergence research: tracing how research unfolds from its roots (February 20, 2026)
  • Analysis of morphology and behavior using deep learning methods
    Principles for Creating Life Functions through Evolutionary Information Assembly (January 13, 2026)

2025

  • Development of a markerless multi-individual tracking system for controlling cannibalistic behavior in crickets
    47th Annual Meeting of the Japanese Society for Comparative Physiology and Biochemistry (December 5, 2025)
  • Morphological quantification using deep learning: Morpho-VAE
    99th Symposium on Science of Form “Shape that brings motion” (November 30, 2025)
  • Visualization of morphological variation using 3D Variational Autoencoder
    34th Annual Meeting of the Japanese Society for Bioimaging
  • Behavioral analysis of double mutant Drosophila larvae using DOLO (Drosophila tracking with YOLO)
    1st Systems Behavioral Science Workshop (May 30, 2025)
  • Estimation of psychological state transitions during/after emergency declarations using energy landscape analysis
    SSTB2025 - Spring School for Theoretical Biology 2025- (February 20, 2025)

2024

  • Proposal of morphological quantitative analysis methods using deep learning
    Annual Meeting of the Japanese Society for Mathematical Biology 2024 (September 12, 2024)
  • Quantification of mouse behavior under social defeat stress using mathematical models
    CPSY TOKYO 2024 (March 28, 2024)
  • Mathematical model of rumination in the brain using Bayesian inference
    Spring School for Theoretical Biology 2024 (February 20, 2024)
  • Mathematical model of rumination in the brain using free energy principle
    11th Annual Meeting of the Quantitative Biology Society (January 6, 2024)

2023

  • Unveiling the enigmatic Middle Devonian vertebrate, Palaeospondylus
    The 3rd Asia Evo Conference Symposium (December 16, 2023)
  • Development of a quantitative analysis method for biological morphology using deep learning
    Statphys28 Satellite meeting Statistical Physics and Information-Processing in Living Systems (August 8, 2023)

2022

  • Morphological feature extraction of primate mandibles using variational autoencoders
    10th Annual Meeting of the Quantitative Biology Society (December 15, 2022)
  • A method for morphological feature extraction based on variational auto-encoder
    60th Annual Meeting of the Biophysical Society of Japan (September 30, 2022)
  • A Deep learning approach for the shape analysis of the primates mandible
    Euro Evo Devo 2022 (June 1, 2022)

šŸ“ Other Achievements

Reviews & Commentary

  • Characterization of biological morphology by using machine learning
    Proceedings of the Physical Society of Japan 75.1 2878-2878 (2020)

Medical AI Related

  • Verification of classification methods for 2D OCT images using two-stage networks
    2nd Japanese Society for Medical AI Academic Conference (January 31, 2020)
    Masahiko Takemura, ā—ÆMasato Tsutsumi, Hiroki Kawai, Kazumi Hakamata, Hideyoshi Fuji