研究室紹介LABORATORY

データ駆動生物学

KEYWORDS

  • データ駆動型アプローチ
  • バイオインフォマティクス
  • システム生物学
  • オミクス解析（ゲノム・エピゲノム・トランスクリプトーム・プロテオーム・メタボローム）
  • シングルセル解析・トランスオミクス
  • ベイズモデリング
  • 機械学習・深層学習
  • 逆強化学習・意思決定モデル
  • 多細胞ダイナミクスの数理解析
  • 疾患ネットワーク・階層的モデル
  • 精神疾患・がん・免疫に関する数理的病態解析
  • 画像解析・空間トランスクリプトミクス
  • トランスオミクス・臓器連関モデリング

HEAD

本田 直樹

教授

研究者総覧

LAB MEMBER

構成員名 役職 研究者総覧
矢田 祐一郎 准教授 研究者総覧
近藤 洋平 特任講師 研究者総覧
紅 朋浩 助教 研究者総覧
太田 亮作 特任助教 研究者総覧
坂口 峻太 特任助教 研究者総覧
藤岡 秀成 特任助教 研究者総覧
大河内 康之 助教 研究者総覧
藤原 真奈 研究員
金子 貴輝 研究員

CONTACT

Email honda.naoki.t1◎f.mail.nagoya-u.ac.jp（送信の際は◎を@に変更してください）
HP データ駆動生物学 独自ホームページ

OUTLINE

データ駆動生物学分野では、統計科学・情報科学・計算科学による数理モデリングと、実験的な生物学のアプローチを融合させ、生命現象の原理解明に取り組んでいます。次世代シークエンサーや質量分析、ライブイメージングなど最先端の計測技術により、膨大なオミクスデータ（ゲノム、エピゲノム、トランスクリプトーム、プロテオーム、メタボロームなど）が取得可能となりましたが、それらを活用するための統合的な解析手法の確立が求められています。 私たちは、生物学的仮説に依存しすぎず、データから現象を読み解く「データ駆動型アプローチ」により、神経・精神疾患やがん、発生、行動などの複雑な生命現象をシステムとして理解することを目指しています。ベイズモデリングや逆強化学習などの数理モデル、機械学習・AI技術、スーパーコンピューティングを活用し、実データと理論を往復しながら生命のしくみに迫ります。

RESEARCH PROJECTS

1. 単細胞・多細胞オミクスデータの統合解析

オミクスデータを対象にした、バッチ統合法・空間再構成法・臓器連関推定法などの開発。最適輸送、深層学習などを駆使し、細胞レベルから個体レベルまで幅広い生命メカニズムの解明に挑んでいます。

2. 認知行動過程や脳神経系のデータ駆動型モデリング

ベイズ推論や強化学習の枠組みを応用して、ヒトや動物の行動データから、意思決定の背後にある心の揺れや戦略の転換を解読する技術の開発を進めています。また、脳の配線情報と遺伝子発現データを統合する解析手法による脳神経回路の配線原理解明にも取り組んでいます。

3. データ駆動型数理モデリングによる病態解析

疾患の進行過程の理解や早期検出、予後予測を目指して、機械学習と数理モデルを駆使したデータ駆動型数理モデリングに取り組んでいます。階層ベイズや状態空間モデル、偏微分方程式などを用いて、バイオマーカーの変化や電子カルテ情報の推移、脳内での物質拡散過程として表される疾患進行過程のモデル化を行い、それに基づいた予測や解析を実現します。

4. 数理モデリングとシミュレーションによる計算生物学

生命現象を数理モデリングとシミュレーションを通して理解することを目指しています。免疫応答の学習過程を予測符号化として捉えるモデルや、幹細胞集団の競争と階層性から生じるダイナミクスの理論化など、実験データと往復しながら生命を支える物理学的・計算論的なロジックに迫ります。

BIBLIOGRAPHY

2025
  1. Tohyama S., Nagashima T., Higashino I., Arima-Yoshida F., Hiyoshi K., Nagase M., Yada Y., Honda N., Watabe A.M.* “Aversive experiences induce valence plasticity of instructive signals to change future learning rules in mice.” Communications Biology, in press.
  2. Cao Z., Setoyama D., Monica-Natsumi D., Matsushima T., Yada Y., Watabe M., Hikida T., Kato A.T., Honda N.* “Leveraging Machine Learning to Uncover the Hidden Links between Trusting Behavior and Biological Markers.” Dialogues in Clinical Neuroscience 27(1), 201–215 (2025).
  3. Koike J., Yada Y., Hira R., Honda N.* “Sperrfy the brain: A data-driven realization of Sperry's Chemoaffinity theory in the neural connectome.” bioRxiv (2025). [Preprint]
  4. Sakaguchi S., Tsutsumi M. (Co-first), Nishi K., Honda N. “Disentanglement of batch effects and biological signals across conditions in the single-cell transcriptome.” bioRxiv (2025). [Preprint]
  5. Ota R.*, Sakamoto M., Aoki W., Honda N. “Prediction of quantitative function of artificially-designed protein from structural information.” bioRxiv (2025). [Preprint]
  6. Itoh T., Kondo Y.*, Nakayama T., Shinomiya A., Aoki K., Yoshimura T., Honda N. “Inverse signal importance in real exposome: How do biological systems dynamically prioritize multiple environmental signals?” bioRxiv (2025). [Preprint]
2024
  1. Ju H., Skibbe H., Fukui M., Yoshimura S.H., Honda N.* “Machine learning-guided reconstruction of cytoskeleton network from Live-cell AFM Images.” iScience 27, 10110907 (2024).
  2. Takeuchi R.F., Sato A.Y., Ito K.N., Yokoyama H., Miyata R., Ueda R., Kitajima K., Kamaguchi R., Suzuki T., Isobe K., Honda N., Osakada F.* “Posteromedial cortical networks encode visuomotor prediction errors.” bioRxiv (2024). [Preprint]
2023
  1. Nakayama T., Tanikawa M., Okushi Y., Itoh T., Shimmura T., Maruyama M., Yamaguchi T., Matsumiya A., Shinomiya A., Guh Y.J., Chen J., Naruse K., Kudoh H., Kondo Y., Honda N., Aoki K., Nagano A.J., Yoshimura T. “A transcriptional program underlying the circannual rhythms of gonadal development in medaka.” Proceedings of the National Academy of Sciences 120(52), e2313514120 (2023).
  2. Yada Y., Honda N. “Few-shot prediction of amyloid β accumulation from mainly unpaired data on biomarker candidates.” npj Systems Biology and Applications 9, 59 (2023).
  3. Sakaguchi S., Okochi Y., Tanegashima C., Nishimura O., Uemura T., Kadota M., Honda N., Kondo T.* “Single-cell transcriptome atlas of Drosophila gastrula 2.0.” Cell Reports 42, 112707 (2023).
  4. Konaka Y., Honda N.* “Decoding reward–curiosity conflict in decision-making from irrational behaviors.” Nature Computational Science 3, 418–432 (2023).
  5. Hatakeyama Y., Saito N., Mii Y., Shinozuka T., Takemoto T., Honda N., Takada S. “Intercellular exchange of Wnt ligands reduces cell population heterogeneity in embryogenesis.” Nature Communications 14, 1924 (2023).
  6. Ishino S., Kamada T., Sarpong G., Kitano J., Tsukasa R., Mukohira H., Sun F., Li Y., Kobayashi K., Honda N., Oishi N., Ogawa M.* “Dopamine error signal to actively cope with lack of expected reward.” Science Advances 9(10), eade5420 (2023).
  7. Ju H., Honda N., Yoshimura S.H., Kaneko M., Shigematsu T., Kiyono K.* “Multidimensional fractal scaling analysis using higher order moving average polynomials and its fast algorithm.” Signal Processing 208, 108997 (2023).
  8. Onishi T., Honda N., Igarashi Y.* “Optimal COVID-19 testing strategy on limited resources.” PLoS ONE 18(2), e0281319 (2023).
  9. Yoshido K., Honda N.* “Adaptive discrimination of antigen risk by predictive coding in immune system.” iScience 26, 105754 (2023).
  10. Honda N. “Data-driven Interpretation of Emotional Fluctuation and Irrationality.” Medical Science Digest, Special Issue: Hikikomori and Psychiatric Disorders, 49(3), 12–15 (2023). [Japanese] [Review Articles]
2022
  1. Nakamuta S., Yoshido K., Honda N.* “Stem cell homeostasis regulated by hierarchy and neutral competition.” Communications Biology 5, 1268 (2022).
  2. Kanatsu-Shinohara M., Honda N., Tanaka T., Tatehana M., Kikkawa T., Osumi N., Shinohara T.* “Regulation of male germline transmission patterns by the Trp53-Cdkn1a pathway.” Stem Cell Reports 17, 1–18 (2022).
  3. Okochi Y., Matsui T., Sakaguchi S., Kondo T., Honda N. “Zero-shot reconstruction of mutant spatial transcriptomes.” bioRxiv (2022). [Preprint]
2021
  1. Okochi Y., Sakaguchi S., Nakae K., Kondo T., Honda N.* “Model-based prediction of spatial gene expression via generative linear mapping.” Nature Communications 12, 3731 (2021).
  2. Asakura Y., Kondo Y., Aoki K., Honda N.* “Hierarchical modeling of mechano-chemical dynamics of epithelial sheets across cells and tissue.” Scientific Reports 11, 4069 (2021).
  3. Honda N. “Data-driven Biology: Mathematical Modeling Rooted in Data.” Sugaku Kagaku (Mathematical Sciences), Special Issue: Mathematical Modeling and Life Science, September 2021. [Japanese] [Review Articles]
2020
  1. Honda N.*, Matsui T. “Somite boundary determination in normal and clock-less vertebrate embryos.” Development, Growth & Differentiation 62, 177–187 (2020).
  2. Honda N. “Modeling and Data Analysis of Animal Behavior Based on Reinforcement and Inverse Reinforcement Learning.” Jikken Igaku (Experimental Medicine), Supplement “Applying Machine Learning to Life Science,” 38(20), 202–209 (2020). [Japanese] [Review Articles]
  3. Okouchi Y., Sakaguchi S., Honda N. “Machine Learning-Based Spatial Gene Expression Reconstruction from scRNA-seq Data.” Jikken Igaku (Experimental Medicine), Supplement “Applying Machine Learning to Life Science,” 38(20), 63–69 (2020). [Japanese] [Review Articles]
2019
  1. Honda N.*, Akiyama R., Sari D.W.K., Ishii S., Bessho Y., Matsui T. “Noise-resistant developmental reproducibility in vertebrate somite formation.” PLoS Computational Biology 15(2), e1006579 (2019).
  2. Honda N. “Wiring Principles from Axonal Chemotaxis to Neural Circuit Formation.” Seibutsu Butsuri (Biophysics) 59(3), 141–143 (2019). [Japanese] [Review Articles]
  3. Honda N. “4-2 Gephi: Intuitive Layout of Mouse Brain Neural Network Structures.” In: Professional Data Visualization Techniques – Beyond Excel (Ed. Yasunobu Igarashi), 2019. [Japanese] [Books].
2018
  1. Sari D.W.K., Akiyama R., Honda N., Ishijima H., Bessho Y., Matsui T.* “Time-lapse observation of stepwise regression of Erk activity in zebrafish presomitic mesoderm.” Scientific Reports 8, 4335 (2018).
  2. Yamaguchi S., Honda N.*, Ikeda M., Tsukada Y., Nakano S., Mori I., Ishii S. “Identification of animal behavioral strategies by inverse reinforcement learning.” PLoS Computational Biology 14(5), e1006122 (2018).
  3. Honda N. “Chapter 7: Identification of Biological Information Processing Based on Quantitative Data.” In: Advances in Biotechnology via AI Integration (Ed. Mitsuyoshi Ueda), 2018. [Japanese] [Books].
2017
  1. Kanatsu-Shinohara M.*, Honda N., Shinohara T. “Nonrandom contribution of left and right testes to germline transmission from mouse spermatogonial stem cells.” Biology of Reproduction 97(6), 902–910 (2017).
  2. Aoki K.*, Kondo Y., Honda N., Hiratsuka T., Ito R.E., Matsuda M. “Propagating wave of ERK activation orients collective cell migration.” Developmental Cell 43, 305–317 (2017).
  3. Honda N.* “Revisiting chemoaffinity theory: Chemotactic implementation of topographic axonal projection.” PLoS Computational Biology 13(8), e1005702 (2017).
  4. Takano T., Wu M., Nakamuta S., Honda N., Ishizawa N., Namba T., Watanabe T., Xu C., Hamaguchi T., Yura Y., Amano M., Hahn K.M., Kaibuchi K.* “Discovery of long-range inhibitory signaling to ensure single axon formation.” Nature Communications 8, 33 (2017).
  5. Honda N.*, Uegaki K., Ishii S. “Self-organization mechanism of microtubule orientation patterns in axons and dendrites.” bioRxiv 163014 (2017). [Preprint]
  6. Shinohara M., Honda N., Shinohara T. “Mechanisms for Maintaining the Functional Lifespan of Spermatogonial Stem Cells.” Jikken Igaku (Experimental Medicine) 35(8), 1297–1302 (2017). [Japanese] [Review Articles]
2016
  1. Honda N., Nishiyama M., Togashi K., Igarashi Y., Hong K., Ishii S. “Multi-phasic bi-directional chemotactic responses of the growth cone.” Scientific Reports 6, 36256 (2016).
  2. Yamao M., Aoki K., Yukinawa N., Ishii S., Matsuda M., Honda N.* “Two new FRET imaging measures: linearly proportional to and highly contrasting the fraction of active molecules.” PLoS One 11(10), e0164254 (2016).
  3. Li Y., Nakae K., Ishii S., Honda N.* “Uncertainty-dependent extinction of fear memory in an amygdala-mPFC neural circuit model.” PLoS Computational Biology 12(9), e1005099 (2016).
  4. Kanatsu-Shinohara M.*, Honda N., Shinohara T. “Nonrandom germline transmission of mouse spermatogonial stem cells.” Developmental Cell 38, 248–261 (2016).
  5. Tsukada Y., Yamao M., Honda N., Shimowada T., Ohnishi N., Kuhara A., Ishii S., Mori I.* “Reconstruction of spatial thermal gradient encoded in thermosensory neuron AFD in Caenorhabditis elegans.” Journal of Neuroscience 36(9), 2571–2581 (2016).
2015～2005
  1. Yamao M., Honda N.* (Co-first), Kunida K., Aoki K., Matsuda M., Ishii S.* “Distinct predictive performance of Rac1 and Cdc42 in cell migration.” Scientific Reports 5, 17527 (2015).
  2. Kumagai Y., Honda N., Nakasyo E., Kamioka Y., Kiyokawa E., Matsuda M.* “Heterogeneity in ERK activity as visualized by in vivo FRET imaging of mammary tumor cells developed in MMTV-Neu mice.” Oncogene 34(8), 1051–1057 (2015).
  3. Hiratsuka T., Fujita Y., Honda N., Aoki K., Kamioka Y., Matsuda M.* “Intercellular propagation of extracellular signal-regulated kinase activation revealed by in vivo imaging of mouse skin.” eLife 4, e05178 (2015).
  4. Yukinaga H., Shionyu C., Hirata E., Ui-Tei K., Nagashima T., Kondo S., Okada-Hatakeyama M., Honda N., Matsuda M.* “Fluctuation of Rac1 activity is associated with the phenotypic and transcriptional heterogeneity of glioma cells.” Journal of Cell Science 127(8), 1805–1815 (2014).
  5. Honda N.*, Ishii S. “Mathematical Modeling of Neuronal Polarization During Development.” Progress in Molecular Biology and Translational Science 123, 127–141 (2014).
  6. Honda N., Yamao M., Ishii S. “System Identification of Cell Migration.” Seitai no Kagaku (Science of the Living Body) 65(5), 468–469 (2014). [Japanese] [Review Articles]
  7. Yamao M., Honda N., Ishii S. “Chapter 11: Collective Cell Migration.” In: Trends in Biophysics: From Cell Dynamics Toward Multicellular Growth Phenomena (Ed. Pavel Kraikivski), pp. 205–235 (2013). [Books]
  8. Kaneko-Kawano T.*, Takasu F., Honda N., Sakumura Y., Ishii S., Ueba T., Eiyama A., Okada A., Kawano Y., Suzuki K. “Dynamic Regulation of Myosin Light Chain Phosphorylation by Rho-kinase.” PLoS One 7(6), e39269 (2012).
  9. Yamao M., Honda N.*, Ishii S. “Multi-cellular logistics of collective cell migration.” PLoS One 6(12), e27950 (2011).
  10. Nonaka S., Honda N.* (Co-first), Ishii S. “A multiphysical model of cell migration integrating reaction-diffusion, membrane and cytoskeleton.” Neural Networks 24, 979–989 (2011).
  11. Honda N.*, Nakamuta S., Kaibuchi K., Ishii S. “Flexible Search for Single-Axon Morphology during Neuronal Spontaneous Polarization.” PLoS One 6(4), e19034 (2011).
  12. Yamao M., Honda N., Ishii S. “Noise-Induced collective migration for neural crest cells.” Lecture Notes in Computer Science 6352, 155–163 (2010).
  13. Honda N.*, Sakumura Y., Ishii S. “Stochastic control of spontaneous signal generation for gradient sensing in chemotaxis.” Journal of Theoretical Biology 255, 259–266 (2008).
  14. Tamura H., Ng D.C., Tokuda T., Honda N., Nakagawa T., Mizuno T., Hatanaka Y., Ishikawa Y., Ohta J., Shiosaka S.* “One-chip sensing device (biomedical photonic LSI) enabled to assess hippocampal steep and gradual up-regulated proteolytic activities.” Journal of Neuroscience Methods 173, 114–120 (2008).
  15. Honda N., Sakumura Y., Ishii S.* “Local signaling with molecular diffusion as a decoder of Ca²⁺ signals in synaptic plasticity.” Molecular Systems Biology 1, 2005.0027 (2005).

ページの一番上へ戻る