Prediction and analysis of multiple protein lysine modified sites based on conditional wasserstein generative adversarial networks
Abstract Background Protein post-translational modification (PTM) is a key issue to investigate the mechanism of protein’s function. With the rapid development of proteomics technology, a large amount of protein sequence data has been generated, which highlights the importance of the in-depth study...
Main Authors: | Yingxi Yang, Hui Wang, Wen Li, Xiaobo Wang, Shizhao Wei, Yulong Liu, Yan Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2021-03-01
|
Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12859-021-04101-y |
Similar Items
-
Prediction and analysis of multiple protein lysine modified sites based on conditional wasserstein generative adversarial networks
by: Li, W., et al.
Published: (2021) -
Deep Generative Adversarial Networks for Image-to-Image Translation: A Review
by: Aziz Alotaibi
Published: (2020-10-01) -
An Information Entropy-Based Approach for Computationally Identifying Histone Lysine Butyrylation
by: Guohua Huang, et al.
Published: (2020-02-01) -
Reconstruction of shale image based on Wasserstein Generative Adversarial Networks with gradient penalty
by: Wenshu Zha, et al.
Published: (2020-03-01) -
RF-MaloSite and DL-Malosite: Methods based on random forest and deep learning to identify malonylation sites
by: Hussam AL-barakati, et al.
Published: (2020-01-01)