Yamane T, Nakayama T, Ekimoto T, Inoue M, Ikezaki K, Sekiguchi H, Kuramochi M, Terao Y, Judai K, Saito M, Ikeguchi M, C. Sasaki Y ,Comparison of the Molecular Motility of Tubulin Dimeric Isoforms: Molecular Dynamics Simulations and Diffracted X-ray Tracking Study, International Journal of Molecular Sciences , 2,415,423,2023/10/2, https://www.mdpi.com/1422-0067/24/20/15423
論文
Echizen H, Hanaoka K, Shimamoto K, Hibi R, Toma-Fukai S, Ohno H, Sasaki E, Komatsu T, Ueno T, Tsuchiya Y, Watanabe Y, Otsuka T, Saito H, Nagatoishi S, Tsumoto K, Kojima H, Okabe T, Shimizu T, Urano Y,”Discovery of a cystathionine γ-lyase (CSE) selective inhibitor targeting active-site pyridoxal 5′-phosphate (PLP) via Schiff base formation”, Scientific Reports ,1,316,456,2023/9/30, https://doi.org/10.1038/s41598-023-43536-6
Okamoto R,Kojima R, Nakatsui M , Toward AI-supported evaluation for safety control measures against near-miss events in pharmaceutical products , Safety Science , Volume 168,106314 , 2023/12/1 , doi.org/10.1016/j.ssci.2023.106314
Hattori EY, Arakawa Y, Mineharu Y, Furukawa K, Terada Y, Yamao Y, Tanji M, Kikuchi T, Miyamoto S. , Seizure control by adding on other anti-seizure medication on seizure during levetiracetam administration in patients with glioma-related epilepsy. , BMC Cancer , 23, 849 , 2023/9/11 , doi.org/10.1186/s12885-023-11273-8
Nakamura K, Uchino E, Sato N, Araki A, Terayama K, Kojima R, Murashita K, Itoh K, Mikami T, Tamada Y, Okuno Y , Individual health-disease phase diagrams for disease prevention based on machine learning , Journal of Biomedical Informatics , 144,104448 , 2023/8/23 , doi.org/10.1016/j.jbi.2023.104448
Matsuoka T, Hattori A, Oishi S, Araki M, Biao Ma, Fujii T, Arichi N, Okuno Y, Kakeya H, Yamasaki S, Ohno H, Inuki S , Establishment of an MR1 Presentation Reporter Screening System and Identification of Phenylpropanoid Derivatives as MR1 Ligands. , Journal of medicinal chemistry , 66(17),12520–12535 , 2023/8/23 , doi.org/10.1021/acs.jmedchem.3c01122
Nojima S#*, Kadoi T, Suzuki A, Kato C, Ishida S, Kido K, Fujita K, Okuno Y, M. Hirokawa, K. Terayama*, Morii E, , Deep-learning-based differential diagnosis of follicular thyroid tumors using histopathological images , Modern Pathology ,100296,2023/7/31, DOI: 10.1016/j.modpat.2023.100296
Aya Nakamura, Ryosuke Kojima, Yuji Okamoto, Eiichiro Uchino, Yohei Mineharu, Yohei Harada, Mayumi Kamada, Manabu Muto, Motoko Yanagita, Yasushi Okuno , A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data. , arXiv:2307.11487 , 2023/7/21 , https://doi.org/10.48550/arXiv.2307.11487
Koyama T, Matsumoto S, Iwata H, Kojima R, Okuno Y. , Improving Compound–Protein Interaction Prediction by Self-Training with Augmenting Negative Samples , Journal of Chemical Information and Modeling , , 63, 15 , 4552–4559 , 2023/7/17 , https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c00269
Hatano N, Kamada M, Kojima R, Okuno Y , Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network. , bioRxiv , 2023/7 , https://doi.org/10.1101/2023.07.05.547896