Maqola

Predicting the activity and properties of chemicals based on RoBERTa

Davronov Rifqat RahimovichV.I. Romanovsky Institute of Mathematics, Academy of Sciences, Tashkent, UzbekistanSafarov Ro'zmat Abdiqayum O'g'liV.I. Romanovsky Institute of Mathematics, Academy of Sciences, Tashkent, UzbekistanAbdumalikov Shoxrux Qaxramon O'g'liV.I. Romanovsky Institute of Mathematics, Academy of Sciences, Tashkent, Uzbekistan

2021 International Conference on Information Science and Communications Technologies (ICISCT)conference2021en

ABI

Annotatsiya

Machine learning allows us to solve problems by learning big data. In recent years, machine learning has been widely used in various fields, including solving various problems in chemistry. Examples include in computational chemistry, in the discovery of new drugs and even in the prediction of the synthesis of substances. In this work, we propose BPE and RoBERT, the latest technologies in natural language processing, to predict the activity and properties of chemicals. The results obtained were compared with the results given by the ChemBERTa model.

Mavzular

Computational Drug Discovery Methods Machine Learning in Materials Science Advanced Text Analysis Techniques

Identifikatorlar

DOI: 10.1109/icisct52966.2021.9670046

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