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poli 🧪: a library of discrete objective functions

Getting started

Getting started

The basics

What is poli?
Defining an observer
Isolating black box objective functions

Examples

Optimizing protein stability using random mutations

Objective functions

All objective functions
Albuterol Similarity (using TDC)
Aloha objective function
Amlodipine MPO (using TDC)
Celecoxib Rediscovery (using TDC)
Deco Hop (using TDC)
dockstring
DRD2 Docking (using TDC)
DRD3 docking (using TDC)
Fexofenadine MPO (using TDC)
Protein solvent accessibility (using foldx)
Protein stability (using foldx)
GSK3β (using TDC)
Isomer C7H8N2O2 (using TDC)
Isomer C9H10N2O2PF2Cl (using TDC)
Log-solubility (logP)
Median 1 (using TDC)
Median 2 (using TDC)
Mestranol Similarity (using TDC)
Osimetrinib MPO (using TDC)
Penalized logP (using lambo)
Quantitative Estimate of Druglikeness (QED)
Ranolazine MPO (using TDC)
Rapid Stability Predictions
Synthetic Accessibility (using TDC)
Scaffold Hop (using TDC)
Sitagliptin MPO (using TDC)
Thiothixene Rediscovery (using TDC)
Toy continuous objective functions
Troglitazone Rediscovery (using TDC)
Valsartan SMARTS (using TDC)
White Noise objective function
Zaleplon MPO (using TDC)

Optimizers

Random mutations
CMA-ES
Line Bayesian Optimization
Hvarfner’s Vanilla Bayesian Optimization
Sparse Axis-Aligned Subspaces Bayesian Optimization (SAASBO)
Adaptive Linear Embedding Bayesian Optimization (ALEBO)
Trust Region Bayesian Optimization (Turbo)
Adaptively expanding subspaces (BAxUS)
Bounce
Probabilistic Reparametrization

Contributing

Adding a new black box to the repository
Adding a new optimizer to poli-baselines

API reference

API documentation for poli

Bibliography

References

Appendix: Understanding foldx

Installing foldx
Computing the energy of a protein and a single mutation

Repository
Open issue

.rst

poli.objective_repository.gfp_select.register

poli.objective_repository.gfp_select.register#

Classes

`GFPSelectionBlackBox`([batch_size, ...])
`GFPSelectionProblemFactory`()

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By Center for Basic Machine Learning Research in Life Science

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