"Unlocking the Potential of Deep Learning for Advancing Drug Discovery"

Deep learning is becoming increasingly important in the field of drug discovery, with potential applications ranging from target identification and validation to drug design and repurposing. By leveraging the power of deep learning models, researchers are able to better identify potential drug targets, design and optimize drug molecules, and repurpose existing drugs for novel indications.

In particular, deep learning models can be used to identify novel drug targets in large volumes of biological data and then validate drug candidates that act on these targets. Finally, deep learning models can be used to identify repurposing opportunities for existing drugs, allowing for the development of new treatments for diseases that were previously not addressed.

List of Research Papers with insightful information

1. "Deep learning tools for advancing drug discovery and developmental".
2. "Deep learning in drug discovery: an integrative review and future challenges"
3. "Comprehensive Survey of Recent Drug Discovery Using Deep Learning, 2021"
4. "Current methods and challenges for deep learning in drug discovery"
5. "Training recurrent neural networks as generative neural networks for molecular structures: how does it impact drug discovery?"
6. "Trends in Deep Learning for Property-driven Drug Design"
7. "Deep learning in drug discovery: a futuristic modality to materialize the large datasets for cheminformatics"
8. "An overview of neural networks for drug discovery and the inputs used"
9. "The transformational role of GPU computing and deep learning in drug discovery"
10. "Drug discovery with explainable artificial intelligence"
11. "Using deep neural networks to explore chemical space"

Happy learning 😄

For more bioinformatics news and updates, Join our telegram channel.
Click the link to join: https://t.me/llbschool.