Application of Deep Neural Networks in Protein Structure Analysis
Keywords:
bioinformatics, deep neural networks, protein structure, artificial intelligenceAbstract
The article presents an innovative approach to protein structure analysis using deep neural networks. Deep learning techniques were employed to predict the tertiary structure of proteins based on amino acid sequences, achieving significant accuracy improvement compared to traditional methods
References
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., ... & Hassabis, D. (2021). Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583–589. https://doi.org/10.1038/s41586-021-03819-2
Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., ... & Kavukcuoglu, K. (2020). Improved protein structure prediction using potentials from deep learning. Nature, 577(7792), 706–710. https://doi.org/10.1038/s41586-019-1923-7
Wang, S., Sun, S., Li, Z., Zhang, R., & Xu, J. (2017). Accurate de novo prediction of protein contact map by ultra-deep learning model. PLoS Computational Biology, 13(1), e1005324. https://doi.org/10.1371/journal.pcbi.1005324
Li, Y., Hu, J., Zhang, C., Yu, D. J., Zhang, Y., & Wang, Z. (2021). Deep learning in structural bioinformatics: Recent advances and future directions. Briefings in Bioinformatics, 22(5), bbab079. https://doi.org/10.1093/bib/bbab079
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Czasopismo Modern

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.