DeepsmirUD is a deep learning-based framework that uniquely uses connectivity scores to predict whether small molecules will upregulate or downregulate microRNA (miRNA) expression, offering a scalable and sequence-driven approach for RNA-targeted drug discovery.
Whether youβre working in computational drug discovery, bioinformatics, or molecular pharmacology, DeepsmirUD provides a ready-to-use solution for drug screening.
Please check https://2003100127.github.io/deepsmirud for its usage.
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(https://pypi.org/project/deepsmirud)
conda create --name deepsmirud python=3.11 conda activate deepsmirud pip install deepsmirud --upgrade
Sun, J., Ru, J., Ramos-Mucci, L., Qi, F., Chen, Z., Chen, S., Cribbs, A. P., Deng, L., & Wang, X. (2023). DeepsmirUD: Prediction of Regulatory Effects on microRNA Expression Mediated by Small Molecules Using Deep Learning. International journal of molecular sciences, 24(3), 1878. https://doi.org/10.3390/ijms24031878
@article{deepsmirud2023,
TITLE = {DeepsmirUD: Prediction of Regulatory Effects on microRNA Expression Mediated by Small Molecules Using Deep Learning},
AUTHOR = {Sun, Jianfeng and Ru, Jinlong and Ramos-Mucci, Lorenzo and Qi, Fei and Chen, Zihao and Chen, Suyuan and Cribbs, Adam P. and Deng, Li and Wang, Xia},
JOURNAL = {International Journal of Molecular Sciences},
VOLUME = {24},
YEAR = {2023},
NUMBER = {3},
ARTICLE-NUMBER = {1878},
URL = {https://www.mdpi.com/1422-0067/24/3/1878},
PubMedID = {36768205},
ISSN = {1422-0067},
DOI = {10.3390/ijms24031878}
}
