6 papers
MassSpecGym in the Wild: Uncovering and Correcting Evaluation Pitfalls in AI-Driven Molecule Discovery
Hongxuan Liu, Roman Bushuiev, Ivy Lightheart +12
Reliable benchmarking is critical for developing machine learning models for tandem mass spectrometry (MS/MS) based molecule discovery. Subtle issues in experimental design and mod…
One protein is all you need
Anton Bushuiev, Roman Bushuiev, Olga Pimenova +9
Generalization beyond training data remains a central challenge in machine learning for biology. A common way to enhance generalization is self-supervised pre-training on large dat…
De novo generation of functional terpene synthases using TpsGPT
Hamsini Ramanathan, Roman Bushuiev, Matouš Soldát +5
Terpene synthases (TPS) are a key family of enzymes responsible for generating the diverse terpene scaffolds that underpin many natural products, including front-line anticancer dr…
Generalization Beyond Benchmarks: Evaluating Learnable Protein-Ligand Scoring Functions on Unseen Targets
Jakub Kopko, David Graber, Saltuk Mustafa Eyrilmez +4
As machine learning becomes increasingly central to molecular design, it is vital to ensure the reliability of learnable protein-ligand scoring functions on novel protein targets.…
Learning to engineer protein flexibility
Petr Kouba, Joan Planas-Iglesias, Jiri Damborsky +3
Generative machine learning models are increasingly being used to design novel proteins for therapeutic and biotechnological applications. However, the current methods mostly focus…
MassSpecGym: A benchmark for the discovery and identification of molecules
Roman Bushuiev, Anton Bushuiev, Niek F. de Jonge +27
The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is…