Find a runnable biological lab

Multi-model lab with an embedded visualisation sibling for the canonical deterministic Lotka-Volterra predator-prey system.

Beginner-friendly multi-model tutorial lab where users choose a starting plate, watch viable cells grow, and read why starvation changes the curve.

Multi-model lab with an embedded visualisation sibling for AutoDock Vina 1.2.7. Ships with the bundled 1iep receptor/ligand PDBQT pair so the lab runs out of the box.

Multi-model lab with an embedded visualisation sibling for Boltz-2 affinity-focused protein-ligand predictions. Ships with a real protein/ligand pair so the lab runs out of the box on a GPU runner.

Multi-model lab with an embedded visualisation sibling for DiffDock-L 1.1.3 single-complex docking. Ships with the bundled 1a0q receptor and a SMILES ligand so the lab runs out of the box.

Guided Boltz-2 workflow for learning how a protein sequence and ligand SMILES become a predicted complex, binder probability, affinity-like value, confidence metrics, and reproducible report context.

Guided Boltz-2 workflow for exploring a Mycobacterium tuberculosis InhA target with a triclosan reference ligand example, binder probability, affinity-like value, confidence metrics, and reproducible report context.

Guided Boltz-2 workflow for exploring a malaria-related falcipain-2 target with an E-64 reference inhibitor-like ligand example, binder probability, affinity-like value, confidence metrics, and reproducible report context.

Guided Boltz-2 workflow for exploring a cancer-relevant ABL1 kinase domain with an imatinib reference ligand example, binder probability, affinity-like value, confidence metrics, and reproducible report context.

Guided Boltz-2 workflow for ranking a small ligand CSV against one protein target using binder probability, affinity-like value, confidence metrics, flags, and report-ready output.

Guided Boltz-2 workflow for exploring a viral 3C-like protease target with a nirmatrelvir reference ligand example, binder probability, affinity-like value, confidence metrics, and reproducible report context.