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Data-Driven Prediction for Absorption Wavelengths of Microbial Rhodopsins by using Machine Learning Approaches

The applications of AI in biological and medical fields have been rapidly progressing in these decades. In particular, the structural prediction by Alphafold2 drastically changed the situation of structural biology. The application of AI, however, in other fields is not so established, and many drastic developments are still being demanded. In this symposium, we will present cutting-edge studies incorporating both AI and experiments in a complementary manner for biological and chemical applications. Given the current situation in each discipline, we will discuss the future perspective of biological discovery and paradigm shift by integrating AI and experimental approaches.

Biophysical Society of Japan

The 61st Annual Meeting of the Biophysical Society of Japan

The 61st Annual Meeting of the Biophysical Society of Japan

[1SAA-2]Data-Driven Prediction for Absorption Wavelengths of Microbial Rhodopsins by using Machine Learning Approaches