Next Generation Sequencing Data Analysis
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From Fragment to Drug Candidate: How Sesame Uses AI to Build Better Molecules
There's a moment in drug discovery that every medicinal chemist knows well. You've found a hit, a molecule that binds to your target, shows...
Can Machine Learning Forecast Antibiotic Resistance Trends Across the Globe?
Antimicrobial resistance (AMR) has quietly become one of the defining health crises of our time, undermining the effectiveness of life-saving medicines and putting decades...
From Natural Language to Biological Design: How Proto Powers Generative Biology
A structured program produced genetic sequences that don't exist in nature — then those sequences were built, tested in human cells, and found to...
DECAF: Genesis AI-Based Framework for Faster and Computationally Efficient All-Atom Protein Cofolding
The high computational cost of generating accurate atomic-level biomolecular structures remains a major challenge in AI-driven drug discovery. Researchers from Genesis Molecular AI, MIT,...
Boltz Launches BoltzMol-1, BoltzProt-1, and a New API for Small Molecule Hit Discovery and...
Drug discovery has always been brutally slow. You pick a target, screen hundreds of thousands of compounds, watch most of them fail, spend months...