査読付き論文等
引用数100以上は赤字、引用数20以上は太字にしています。
(引用数の詳細や論文のダウンロード等はGoogle Scholar Citations から。)
- Keating, S. M., Waltemath, D., König, M., Zhang, F., Dräger, A., Chaouiya, C., Bergmann, F. T., Finney, A., Gillespie, C. S., Helikar, T., Hoops, S., Malik‐Sheriff, R. S., Moodie, S. L., Moraru, I. I., Myers, C. J., Naldi, A., Olivier, B. G., Sahle, S., Schaff, J. C., … Zucker, J. (2020). sbml level 3: An extensible format for the exchange and reuse of biological models. Molecular Systems Biology, 16(8). https://doi.org/10.15252/msb.20199110
- Watabe, M., Yoshimura, H., Arjunan, S. N. V., Kaizu, K., & Takahashi, K. (2020). Signaling activations through G-protein-coupled-receptor aggregations. Physical Review E, 102(3), 032413. https://doi.org/10.1103/PhysRevE.102.032413
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Arjunan, S. N. V., Miyauchi, A., Iwamoto, K., & Takahashi, K. (2020). Pspatiocyte: A high-performance simulator for intracellular reaction-diffusion systems. BMC Bioinformatics, 21(1), 33. https://doi.org/10.1186/s12859-019-3338-8
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Watabe, M., Arjunan, S. N. V., Chew, W. X., Kaizu, K., & Takahashi, K. (2019). Cooperativity transitions driven by higher-order oligomer formations in ligand-induced receptor dimerization. Physical Review E, 100(6), 062407. https://doi.org/10.1103/PhysRevE.100.062407
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Watabe, M., Arjunan, S. N. V., Chew, W. X., Kaizu, K., & Takahashi, K. (2019). Simulation of live-cell imaging system reveals hidden uncertainties in cooperative binding measurements. Physical Review E, 100(1), 010402. https://doi.org/10.1103/PhysRevE.100.010402
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Chew, W.-X., Kaizu, K., Watabe, M., Muniandy, S. V., Takahashi, K., & Arjunan, S. N. V. (2019). Surface reaction-diffusion kinetics on lattice at the microscopic scale. Physical Review E, 99(4), 042411. https://doi.org/10.1103/PhysRevE.99.042411
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Sokolowski, T. R., Paijmans, J., Bossen, L., Miedema, T., Wehrens, M., Becker, N. B., Kaizu, K., Takahashi, K., Dogterom, M., & ten Wolde, P. R. (2019). Egfrd in all dimensions. The Journal of Chemical Physics, 150(5), 054108. https://doi.org/10.1063/1.5064867
- Itaya H, Yamakawa H, Tomita M, Takahashi K, BriCA Kernel: Cognitive Computing Platform for Large-scale Distributed Memory Environments. The 28th Annual Conference of the Japanese Neural Network Society, Okinawa Japan, 26 October 2018.
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Chew, W.-X., Kaizu, K., Watabe, M., Muniandy, S. V., Takahashi, K., & Arjunan, S. N. V. (2018). Reaction-diffusion kinetics on lattice at the microscopic scale. Physical Review E, 98(3), 032418. https://doi.org/10.1103/PhysRevE.98.032418
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Hiroshima, M., Pack, C., Kaizu, K., Takahashi, K., Ueda, M., & Sako, Y. (2018). Transient acceleration of epidermal growth factor receptor dynamics produces higher-order signaling clusters. Journal of Molecular Biology, 430(9), 1386–1401. https://doi.org/10.1016/j.jmb.2018.02.018
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Magi, S., Iwamoto, K., Yumoto, N., Hiroshima, M., Nagashima, T., Ohki, R., Garcia-Munoz, A., Volinsky, N., Von Kriegsheim, A., Sako, Y., Takahashi, K., Kimura, S., Kholodenko, B. N., & Okada-Hatakeyama, M. (2018). Transcriptionally inducible Pleckstrin homology-like domain, family A, member 1, attenuates ErbB receptor activity by inhibiting receptor oligomerization. Journal of Biological Chemistry, 293(6), 2206–2218. https://doi.org/10.1074/jbc.M117.778399
- Yamakawa H, Arakawa N, Takahashi K: Reinterpreting the cortical circuit. In Architectures for Generality & Autonomy Workshop at IJCAI-17; 2017.
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Imai, R., Nozaki, T., Tani, T., Kaizu, K., Hibino, K., Ide, S., Tamura, S., Takahashi, K., Shribak, M., & Maeshima, K. (2017). Density imaging of heterochromatin in live cells using orientation-independent-DIC microscopy. Molecular Biology of the Cell, 28(23), 3349–3359. https://doi.org/10.1091/mbc.e17-06-0359
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Robotic Biology Consortium (including Takahashi, K.,), Yachie, N., & Natsume, T. (2017). Robotic crowd biology with Maholo LabDroids. Nature Biotechnology, 35(4), 310–312. https://doi.org/10.1038/nbt.3758
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Arjunan, S. N. V., & Takahashi, K. (2017). Multi-algorithm particle simulations with spatiocyte. In D. Kihara (Ed.), Protein Function Prediction (Vol. 1611, pp. 219–236). Springer New York. https://doi.org/10.1007/978-1-4939-7015-5_16
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Itaya, K., Takahashi, K., Nakamura, M., Koizumi, M., Arakawa, N., Tomita, M., & Yamakawa, H. (2016). Brica: A modular software platform for whole brain architecture. In A. Hirose, S. Ozawa, K. Doya, K. Ikeda, M. Lee, & D. Liu (Eds.), Neural Information Processing (Vol. 9947, pp. 334–341). Springer International Publishing. https://doi.org/10.1007/978-3-319-46687-3_37
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Iwamoto, K., Shindo, Y., & Takahashi, K. (2016). Modeling cellular noise underlying heterogeneous cell responses in the epidermal growth factor signaling pathway. PLOS Computational Biology, 12(11), e1005222. https://doi.org/10.1371/journal.pcbi.1005222
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Shindo, Y., Iwamoto, K., Mouri, K., Hibino, K., Tomita, M., Kosako, H., Sako, Y., & Takahashi, K. (2016). Conversion of graded phosphorylation into switch-like nuclear translocation via autoregulatory mechanisms in ERK signalling. Nature Communications, 7(1), 10485. https://doi.org/10.1038/ncomms10485
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Takahashi, K., Itaya, K., Nakamura, M., Koizumi, M., Arakawa, N., Tomita, M., & Yamakawa, H. (2015). A generic software platform for brain-inspired cognitive computing. Procedia Computer Science, 71, 31–37. https://doi.org/10.1016/j.procs.2015.12.185
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Karr, J. R., Takahashi, K., & Funahashi, A. (2015). The principles of whole-cell modeling. Current Opinion in Microbiology, 27, 18–24. https://doi.org/10.1016/j.mib.2015.06.004
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Watabe, M., Arjunan, S. N. V., Fukushima, S., Iwamoto, K., Kozuka, J., Matsuoka, S., Shindo, Y., Ueda, M., & Takahashi, K. (2015). A computational framework for bioimaging simulation. PLOS ONE, 10(7), e0130089. https://doi.org/10.1371/journal.pone.0130089
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Shimo, H., Arjunan, S. N. V., Machiyama, H., Nishino, T., Suematsu, M., Fujita, H., Tomita, M., & Takahashi, K. (2015). Particle simulation of oxidation induced band 3 clustering in human erythrocytes. PLOS Computational Biology, 11(6), e1004210. https://doi.org/10.1371/journal.pcbi.1004210
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Feig, M., Harada, R., Mori, T., Yu, I., Takahashi, K., & Sugita, Y. (2015). Complete atomistic model of a bacterial cytoplasm for integrating physics, biochemistry, and systems biology. Journal of Molecular Graphics and Modelling, 58, 1–9. https://doi.org/10.1016/j.jmgm.2015.02.004
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Maeshima, K., Kaizu, K., Tamura, S., Nozaki, T., Kokubo, T., & Takahashi, K. (2015). The physical size of transcription factors is key to transcriptional regulation in chromatin domains. Journal of Physics: Condensed Matter, 27(6), 064116. https://doi.org/10.1088/0953-8984/27/6/064116
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Nishida, K., Ono, K., Kanaya, S., & Takahashi, K. (2014). KEGGscape: A Cytoscape app for pathway data integration. F1000Research, 3, 144. https://doi.org/10.12688/f1000research.4524.1
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Kaizu, K., de Ronde, W., Paijmans, J., Takahashi, K., Tostevin, F., & ten Wolde, P. R. (2014). The berg-purcell limit revisited. Biophysical Journal, 106(4), 976–985. https://doi.org/10.1016/j.bpj.2013.12.030
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Hayashi, K., Pack, C. G., Sato, M. K., Mouri, K., Kaizu, K., Takahashi, K., & Okada, Y. (2013). Viscosity and drag force involved in organelle transport: Investigation of the fluctuation dissipation theorem. The European Physical Journal E, 36(12), 136. https://doi.org/10.1140/epje/i2013-13136-6
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Nozaki, T., Kaizu, K., Pack, C.-G., Tamura, S., Tani, T., Hihara, S., Nagai, T., Takahashi, K., & Maeshima, K. (2013). Flexible and dynamic nucleosome fiber in living mammalian cells. Nucleus, 4(5), 349–356. https://doi.org/10.4161/nucl.26053
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Aoki, K., Takahashi, K., Kaizu, K., & Matsuda, M. (2013). A quantitative model of erk map kinase phosphorylation in crowded media. Scientific Reports, 3(1), 1541. https://doi.org/10.1038/srep01541
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Hihara, S., Pack, C.-G., Kaizu, K., Tani, T., Hanafusa, T., Nozaki, T., Takemoto, S., Yoshimi, T., Yokota, H., Imamoto, N., Sako, Y., Kinjo, M., Takahashi, K., Nagai, T., & Maeshima, K. (2012). Local nucleosome dynamics facilitate chromatin accessibility in living mammalian cells. Cell Reports, 2(6), 1645–1656. https://doi.org/10.1016/j.celrep.2012.11.008
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Mugler, A., Bailey, A. G., Takahashi, K., & Rein ten Wolde, P. (2012). Membrane clustering and the role of rebinding in biochemical signaling. Biophysical Journal, 102(5), 1069–1078. https://doi.org/10.1016/j.bpj.2012.02.005
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Takahashi, K., Tanase-Nicola, S., & ten Wolde, P. R. (2010). Spatio-temporal correlations can drastically change the response of a MAPK pathway. Proceedings of the National Academy of Sciences, 107(6), 2473–2478. https://doi.org/10.1073/pnas.0906885107
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Takahashi, K. (2008). An exact brownian dynamics method for cell simulation. In M. Heiner & A. M. Uhrmacher (Eds.), Computational Methods in Systems Biology (Vol. 5307, pp. 5–6). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-88562-7_3
- Takahashi K: The E-Cell project and challenges in computational systems biology. In Proc NIC workshop. Volume 36; 2007:55–60.
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Takahashi, K., Arjunan, S. N. V., & Tomita, M. (2005). Space in systems biology of signaling pathways—Towards intracellular molecular crowding in silico. FEBS Letters, 579(8), 1783–1788. https://doi.org/10.1016/j.febslet.2005.01.072
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Sugimoto, M., Takahashi, K., Kitayama, T., Ito, D., & Tomita, M. (2005). Distributed cell biology simulations with e-cell system. In A. Konagaya & K. Satou (Eds.), Grid Computing in Life Science (Vol. 3370, pp. 20–31). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32251-1_3
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Takahashi, K., Kaizu, K., Hu, B., & Tomita, M. (2004). A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics, 20(4), 538–546. https://doi.org/10.1093/bioinformatics/btg442
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Takahashi, K., Ishikawa, N., Sadamoto, Y., Sasamoto, H., Ohta, S., Shiozawa, A., Miyoshi, F., Naito, Y., Nakayama, Y., & Tomita, M. (2003). E-Cell 2: Multi-platform E-Cell simulation system. Bioinformatics, 19(13), 1727–1729. https://doi.org/10.1093/bioinformatics/btg221
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Hucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., and the rest of the SBML Forum:, Arkin, A. P., Bornstein, B. J., Bray, D., Cornish-Bowden, A., Cuellar, A. A., Dronov, S., Gilles, E. D., Ginkel, M., Gor, V., Goryanin, I. I., Hedley, W. J., Hodgman, T. C., … Wang, J. (2003). The systems biology markup language (Sbml): A medium for representation and exchange of biochemical network models. Bioinformatics, 19(4), 524–531. https://doi.org/10.1093/bioinformatics/btg015
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Takahashi, K., Yugi, K., Hashimoto, K., Yamada, Y., Pickett, C. J. F., & Tomita, M. (2002). Computational challenges in cell simulation: A software engineering approach. IEEE Intelligent Systems, 17(5), 64–71. https://doi.org/10.1109/MIS.2002.1039834
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Tomita, M., Hashimoto, K., Takahashi, K., Matsuzaki, Y., Matsushima, R., Saito, K., Yugi, K., Miyoshi, F., Nakano, H., Tanida, S., Saito, Y., Kawase, A., Watanabe, N., Simizu, T. S., & Nakayama, Y. (2000). The E-CELL project: Towards integrative simulation of cellular processes. New Generation Computing, 18(1), 1–12. https://doi.org/10.1007/BF03037563
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Tomita, M., Hashimoto, K., Takahashi, K., Shimizu, T., Matsuzaki, Y., Miyoshi, F., Saito, K., Tanida, S., Yugi, K., Venter, J., & Hutchison, C. (1999). E-CELL: Software environment for whole-cell simulation. Bioinformatics, 15(1), 72–84. https://doi.org/10.1093/bioinformatics/15.1.72
- Tomita M, Shimizu T, Saito K, Venter JC, Hashimoto K, Matsuzaki Y, Tanida S, Hutchison CA, Takahashi K, Miyoshi F, others: E-CELL: Software environment for whole cell simulation. Genome Informatics 1997, 8:147–155.
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Shimizu, T. S., Takahashi, K., & Tomita, M. (1997). CpG distribution patterns in methylated and non-methylated species. Gene, 205(1–2), 103–107. https://doi.org/10.1016/S0378-1119(97)00542-8
その他論文等
- 西田孝三, 海津一成, 高橋恒一, 「パスウェイ可視化のためのダッシュボードコンポーネント」, 可視化情報学会誌, vol. 40, no. 156, pp. 8-13, 2020年1月.
- 三好康祐, 山川宏, 高橋恒一, 「ESNによる階層的予測誤差モデルを用いた音声Local-Global課題の再現シミュレーション」, 信学技報, vol. 119, no. 328, NC2019-46, pp. 61-65, 2019年12月.
- 大澤正彦, 大森隆司, 髙橋恒一, 荒川直哉, 坂井尚行, 上野道彦, 今井倫太, 山川宏, 「AGI開発をナビゲートするための能力マップ」, 2018年度 人工知能学会全国大会(第32回), 鹿児島, 2018年6月.
- 高橋恒一, 「将来の機械知性に関するシナリオと分岐点」, 人工知能学会全国大会論文集 2018, 32:1-4.
- 山川宏, 荒川直哉, 高橋恒一, 「全脳アーキテクチャに必要な新皮質マスターアルゴリズムの検討」, 人工知能学会全国大会論文集 2017
- 渡部匡己, 都築拓, 海津一成, 高橋恒一, 「人工知能による科学研究の加速」, 人工知能学会全国大会論文集 2016, 30:1–4.
- 高橋恒一, 板谷琴音, 中村政義, 「認知コンピューティングのための汎用ソフトウエアプラットフォームの設計と開発」, 人工知能学会全国大会論文集 2015, 29:1–4.
著書等
- 西田孝三,高橋恒一,柚木克之, 「複数のオミクス階層にまたがる大規模パスウェイの2.5次元可視化」実験医学別冊「メタボロミクス実践ガイド」, Eds. 馬場健史,平山明由,松田史生,津川裕司, 羊土社 (2021)
- 黒田玲子, 高橋恒一, 中釜斉, 唐津治夢, 武田計測先端知財団, 「ここまで来ました: 右卷き左卷き・AI駆動科学・がん医療の革新」丸善プラネット (2020)
- 高橋恒一, 「人類を再発明するために必要なこと」, 人工知能美学芸術展 記録集 (人工知能美学芸術研究会), p108-109 (2019) ISBN978-4-9902903-7-5
- 高橋恒一, 「第五の科学 自動化」In AI事典 第3版. 近代科学社 (2019)
- 高橋恒一, 「将来の機械知性に関するシナリオと分岐点」, 人工知能, Vol 33, No. 6. (2018).
- 高橋恒一, 草刈ミカ, 中ザワヒデキ, 「特集「AIと美学・芸術」にあたって」, 人工知能, Vol 33, No. 6. (2018).
- 上野聡, 高橋恒一, 中田秀基, 「特集「AI 計算資源」にあたって」, 人工知能 Vol 33, No. 1. (2018).
- 高橋恒一, 渡部匡己, 「現代科学を超えて―AI駆動型科学へ」 実験医学別冊 「あなたのラボにAI(人工知能)×ロボットがやってくる」, Eds. 夏目徹, 羊土社 (2017)
- 高橋恒一, 井上智洋, 「特集「AI社会論」にあたって」, 人工知能, Vol 32, No. 5. (2017)
- Hibino K, Kaizu K, Takahashi K, and Maeshima K, A Combination Approach Based on Live-Cell Imaging and Computational Modeling to Further Our Understanding of Chromatin, Epigenetics, and the Genome, In Epigenetics and Systems Biology, Eds. Ringrose L, Academic Press (2017)
- 高橋恒一, 「学際的な知見の融合・共創による人工知能技術開発」, 赤門マネジメント・レビュー 15巻12号 (2016)
- 海津一成, 高橋恒一, 「分子はどこまで正確に情報を伝えられるのか」, 生物物理, 56(6):324–326. (2016)
- 今井亮輔, 海津一成, 野崎慎, 前島一博, 高橋恒一, 「定量的1分子蛍光イメージングと計算機シミュレーションを用いたゲノムダイナミクスの解析」, 生化学, Vol.86 No.2 pp.192-200 (2014)
- 岩本一成, 海津一成, 高橋恒一, 「生化学反応ネットワークのシミュレーション」, 生体の科学, Vol.65 No.5 pp.446-447 (2014)
- Addy N, and Takahashi K, Foundations of E-Cell Simulation Environment Architecture, In E-Cell System – Basic Concepts and Applications, Eds. Arjunan S.N.V., Dhar P, and Tomita M, Landes Biosciences (2013).
- 高橋恒一, 「1分子粒度細胞シミュレーション」 シミュレーション辞典, Eds. 日本シミュレーション学会 (コロナ社) (2012).
- 高橋恒一, 海津一成, 「細胞シミュレーション – 計算機上での細胞機能の再構成」 実験医学増刊 Vol.29 No.7 「細胞を創る・生命システムを創る」, Eds.上田泰己、竹内昌治 (羊土社) (2011).
- 高橋恒一, 「システム生物学」 計算力学シミュレーションハンドブック – 超ペタスケールコンピューティングの描像, Eds. 小柳義夫, 土居範久, 松田卓也, 矢川元基, (丸善) (2009).
- Dhar P, Takahashi K, Nakayama Y, and Tomita M, Computer Simulation of the Cell, Encyclopedia of Molecular Cell Biology and Molecular Medicine, Wiley VCH, (2003)