Must Read
Revolutionizing Molecular Linker Design with DiffLinker: The Power of Equivariant 3D-conditional Diffusion Models
The effective paradigm of molecular linkers in drug discovery is crucial for obtaining relevant candidate molecules in early-stage drug development. In this study, researchers...
Unleash the Power of PPI3D: A Comprehensive Web Server to Explore, Analyze, and Model...
Understanding molecular mechanisms requires an understanding of protein interactions with nucleic acids. Researchers can query preprocessed and clustered structural data, analyze the data, and...
Untangling the Cellular Family Tree: GEMLI Estimates Lineage from scRNA-seq Data
Researchers from the Institute of Bioengineering, Lausanne, Switzerland, introduce GEMLI, a powerful computational tool that enables robust identification of cell lineages solely from scRNA-seq...
Smart Sampling for Smarter Drugs: How Active Learning Boosts Drug Discovery
In computational drug discovery, active learning (AL) is a potent approach that makes it possible to identify the best binders from large chemical libraries....
UC Berkeley’s Breakthrough RNA Language Models Predict Mutations that Enhance RNA Function
A new tool from UC Berkeley can predict mutations that can improve the way how RNA works. By leveraging hyperthermophilic RNAs, the researchers identified...