Reference (Oct-20-A4)
References:
1. Li, H., Tian, S., Li, Y., Fang, Q., Tan, R., Pan, Y., … & Gao, X. (2020). Modern deep learning in bioinformatics. Journal of molecular cell biology.
2. Fang, Z., Tan, J., Wu, S., Li, M., Wang, C., Liu, Y., & Zhu, H. (2020). PlasGUN: gene prediction in plasmid metagenomic short reads using deep learning. Bioinformatics, 36(10), 3239-3241. Software available at: http://cqb.pku.edu.cn/ZhuLab/PlasGUN/
3. Wang, D., Liu, D., Yuchi, J., He, F., Jiang, Y., Cai, S., … & Xu, D. (2020). MusiteDeep: a deep-learning based webserver for protein posttranslational modification site prediction and visualization. Nucleic Acids Research. https://www.musite.net
4. Liu, Q., Chen, J., Wang, Y., Li, S., Jia, C., Song, J., & Li, F. (2020). DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites. Briefings in Bioinformatics. Tool is available at: https://deeptorrent.erc.monash.edu/help.html
5. Geoffrey AS, B., Valluri, P. P., Sanker, A., Madaj, R., Davidd, H. A., Malgija, B., … & Mittal, B. (2020). Compound2Drug–a
Machine/deep Learning Tool for Predicting the Bioactivity of PubChem Compounds. Program can be found in the GitHub repository: https://github.com/bengeof/Compound2Drug
6. Min, S., Lee, B., & Yoon, S. (2017). Deep learning in bioinformatics. Briefings in bioinformatics, 18(5), 851-869.
7. Cover Image: https://blog.re-work.co/deep-learning-peter-sadowski/
