DeepHelicon was published in Journal of Structural Biology in July 2020. This work is a major component of Jianfeng Sun’s PhD dissertation (Sun (2021)), which were conducted during his PhD research.
Please cite this work (.bib) below.
@article{SUN20200711,
author = {Jianfeng Sun and Dmitrij Frishman},
doi = {https://doi.org/10.1016/j.jsb.2020.107574},
issn = {1047-8477},
issue = {1},
journal = {Journal of Structural Biology},
keywords = {Deep learning,Molecular evolution,Molecular modeling,Protein structure prediction,Sequence analysis},
pages = {107574},
title = {DeepHelicon: Accurate prediction of inter-helical residue contacts in transmembrane proteins by residual neural networks},
volume = {212},
url = {http://www.sciencedirect.com/science/article/pii/S1047847720301477},
year = {2020},
}- Sun, J., & Frishman, D. (2020). DeepHelicon: Accurate prediction of inter-helical residue contacts in transmembrane proteins by residual neural networks. Journal of Structural Biology, 212(1), 107574. https://doi.org/10.1016/j.jsb.2020.107574
- Sun, J. (2021). Prediction of residue contacts and interaction sites in transmembrane proteins using deep learning (p. 140) [Phdthesis, Technische Universität München]. https://mediatum.ub.tum.de/1577512