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Protein Language Models for drug discovery
Keywords Transformer, Protein interaction, Language model, drug target identification  +
Level Master  +
OneLineSummary Leveraging the sequence-based transformer protein language model for improving potential drug targets identification  +
References Chen, J., Gu, Z., Xu, Y., Deng, M., Lai, LChen, J., Gu, Z., Xu, Y., Deng, M., Lai, L. and Pei, J., 2023. QuoteTarget: A sequence‐based transformer protein language model to identify potentially druggable protein targets. Protein Science, 32(2), p.e4555. Chen, L., Fan, Z., Chang, J., Yang, R., Hou, H., Guo, H., Zhang, Y., Yang, T., Zhou, C., Sui, Q. and Chen, Z., 2023. Sequence-based drug design as a concept in computational drug design. Nature Communications, 14(1), p.4217. Chen, D., Liu, J. and Wei, G.W., 2024. Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions. Nature Machine Intelligence, 6(7), pp.799-810. Jiang, J., Chen, L., Ke, L., Dou, B., Zhang, C., Feng, H., Zhu, Y., Qiu, H., Zhang, B. and Wei, G., 2024. A review of transformers in drug discovery and beyond. Journal of Pharmaceutical Analysis, p.101081.rnal of Pharmaceutical Analysis, p.101081.
StudentProjectStatus Open  +
Supervisors Prayag Tiwari + , Ali Amirahmadi +
TimeFrame Fall 2024  +
Title Protein Language Models for drug discovery  +
Categories StudentProject  +
Modification dateThis property is a special property in this wiki. 25 September 2024 08:58:10  +
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