Application of Deep Neural Networks in Protein Structure Analysis

Authors

  • admin admin

Keywords:

bioinformatics, deep neural networks, protein structure, artificial intelligence

Abstract

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

Published

2025-04-10

How to Cite

admin, admin. (2025). Application of Deep Neural Networks in Protein Structure Analysis. Czasopismo Modern, (1), 1–15. Retrieved from https://trrest.vot.pl/szablony_demonstracyjne/index.php/cm/article/view/12

Issue

Section

Articles