💻 Platform
🧭 Overview
Drutai is a deep learning–based framework for predicting interactions between small molecule drugs and protein targets. It gains high accuracy due to its integration of multiple deep learning methods and informative features.
Whether you’re working in computational drug discovery, bioinformatics, or molecular pharmacology, Drutai provides a ready-to-use solution for high-accuracy DTI prediction.
📔 Documentation
Please check https://2003100127.github.io/drutai for its usage.
🛠️ Installation
-
(https://pypi.org/project/drutai)
conda create --name drutai python=3.11 conda activate drutai pip install drutai --upgrade
📚 Citation
Sun, J., Xu, M., Ru, J., James-Bott, A., Xiong, D., Wang, X., & Cribbs, A. P. (2023). Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications. European journal of medicinal chemistry, 257, 115500. https://doi.org/10.1016/j.ejmech.2023.115500
@article{Sun2023,
title = {Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications},
author = {Jianfeng Sun and Miaoer Xu and Jinlong Ru and Anna James-Bott and Dapeng Xiong and Xia Wang and Adam P. Cribbs},
journal = {European Journal of Medicinal Chemistry},
volume = {257},
pages = {115500},
year = {2023},
issn = {0223-5234},
doi = {https://doi.org/10.1016/j.ejmech.2023.115500},
url = {https://www.sciencedirect.com/science/article/pii/S022352342300466X},
keywords = {microRNA targets, Drug discovery, Molecular interactions, Disease implications, Deep learning},
}
🏠 Developer
📧 Contact
Release files for drutai 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| drutai-0.0.1.tar.gz | 24.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| drutai-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 49.7 kB
Release files / drutai-0.0.1.tar.gz
| Download URL | drutai-0.0.1.tar.gz |
|---|---|
| Size | 24.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.2 CPython/3.11.11 Linux/6.8.0-1021-azure
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Release files / drutai-0.0.1-py3-none-any.whl
| Download URL | drutai-0.0.1-py3-none-any.whl |
|---|---|
| Size | 25.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.2 CPython/3.11.11 Linux/6.8.0-1021-azure
|