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Ryosuke Kojima

Showing results (11-20 of 97) with videos related to

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Chemical & Pharmaceutical Bulletin|August 12, 2025
Elucidating the Light-Emitting Species Generated from Aminoluciferin in Firefly/Beetle BioluminescenceHideo Takakura, Ryosuke Kojima, Takeaki Ozawa, et al.
International Journal of Medical Informatics|January 20, 2020
Prediction of blood pressure variability using deep neural networksHiroshi Koshimizu, Ryosuke Kojima, Kazuomi Kario, et al.
BMC Bioinformatics|October 10, 2023
Network-based prediction approach for cancer-specific driver missense mutations using a graph neural networkNarumi Hatano, Mayumi Kamada, Ryosuke Kojima, et al.
Analytical Chemistry|August 1, 2022
Measuring the pH of Acidic Vesicles in Live Cells with an Optimized Fluorescence Lifetime Imaging ProbeKinuko Koda, Sascha Keller, Ryosuke Kojima, et al.
The Journal of Toxicological Sciences|April 30, 2023
Development of a GCN-based model to predict in vitro phototoxicity from the chemical structure and HOMO-LUMO gapYoshinobu Igarashi, Suyong Re, Ryosuke Kojima, et al.
Plos One|August 31, 2022
Characterizing eye-gaze positions of people with severe motor dysfunction: Novel scoring metrics using eye-tracking and video analysisMari Okamoto, Ryosuke Kojima, Akihiko Ueda, et al.
Chembiochem : a European Journal of Chemical Biology|June 9, 2012
Development of 5'- and 7'-substituted luciferin analogues as acid-tolerant substrates of firefly luciferaseHideo Takakura, Ryosuke Kojima, Takeaki Ozawa, et al.
Journal of Chemical Information and Modeling|November 27, 2019
Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional NetworksShoichi Ishida, Kei Terayama, Ryosuke Kojima, et al.
Journal of Chemical Information and Modeling|March 8, 2022
AI-Driven Synthetic Route Design Incorporated with Retrosynthesis KnowledgeShoichi Ishida, Kei Terayama, Ryosuke Kojima, et al.
Communications Chemistry|October 1, 2025
Transfer learning from custom-tailored virtual molecular databases to real-world organic photosensitizers for catalytic activity predictionNaoki Noto, Taiki Nagano, Mikito Fujinami, et al.
Pageof 10

Showing results (11-20 of 97) with videos related to

Sort By:
Pageof 10
Chemical & Pharmaceutical Bulletin|August 12, 2025
Elucidating the Light-Emitting Species Generated from Aminoluciferin in Firefly/Beetle BioluminescenceHideo Takakura, Ryosuke Kojima, Takeaki Ozawa, et al.
International Journal of Medical Informatics|January 20, 2020
Prediction of blood pressure variability using deep neural networksHiroshi Koshimizu, Ryosuke Kojima, Kazuomi Kario, et al.
BMC Bioinformatics|October 10, 2023
Network-based prediction approach for cancer-specific driver missense mutations using a graph neural networkNarumi Hatano, Mayumi Kamada, Ryosuke Kojima, et al.
Analytical Chemistry|August 1, 2022
Measuring the pH of Acidic Vesicles in Live Cells with an Optimized Fluorescence Lifetime Imaging ProbeKinuko Koda, Sascha Keller, Ryosuke Kojima, et al.
The Journal of Toxicological Sciences|April 30, 2023
Development of a GCN-based model to predict in vitro phototoxicity from the chemical structure and HOMO-LUMO gapYoshinobu Igarashi, Suyong Re, Ryosuke Kojima, et al.
Plos One|August 31, 2022
Characterizing eye-gaze positions of people with severe motor dysfunction: Novel scoring metrics using eye-tracking and video analysisMari Okamoto, Ryosuke Kojima, Akihiko Ueda, et al.
Chembiochem : a European Journal of Chemical Biology|June 9, 2012
Development of 5'- and 7'-substituted luciferin analogues as acid-tolerant substrates of firefly luciferaseHideo Takakura, Ryosuke Kojima, Takeaki Ozawa, et al.
Journal of Chemical Information and Modeling|November 27, 2019
Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional NetworksShoichi Ishida, Kei Terayama, Ryosuke Kojima, et al.
Journal of Chemical Information and Modeling|March 8, 2022
AI-Driven Synthetic Route Design Incorporated with Retrosynthesis KnowledgeShoichi Ishida, Kei Terayama, Ryosuke Kojima, et al.
Communications Chemistry|October 1, 2025
Transfer learning from custom-tailored virtual molecular databases to real-world organic photosensitizers for catalytic activity predictionNaoki Noto, Taiki Nagano, Mikito Fujinami, et al.
Pageof 10