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Tutorials

Explore GraphFLA with twelve datasets, from protein, enzyme and RNA evolution to chemical reactions, materials, neural architectures and compiler settings. Each tutorial takes you from preparing the data to building a landscape and interpreting its analysis.

Choose an optimization problem below. Every page includes Python code, saved results, a downloadable notebook with its data, and a link to run it in Google Colab.

Tutorial Study / dataset Variables Objective Colab
Protein engineering GB1 · Protein G domain B1 Amino acids at positions 39, 40, 41 and 54 Maximise IgG-Fc binding fitness Open In Colab
Antibiotic resistance evolution DHFR · Trimethoprim selection in E. coli Nine nucleotides in codons 26, 27 and 28 Maximise fitness under trimethoprim Open In Colab
Ribozyme evolution Ribozymes · HDV and class III ligase Nucleotides at 14 variable positions Maximise log₁₀ ligase activity Open In Colab
Chemical reaction optimization Suzuki–Miyaura coupling Ligand, base and solvent Maximise UV product-area percentage Open In Colab
Reaction process optimization Electrochemical flow hydrogenation Concentration, temperature and residence time Maximise the reported integrated index Open In Colab
Alloy composition optimization Tungsten–rhenium–osmium alloys Tungsten and rhenium fractions, with osmium as the remainder Maximise high-temperature hardness Open In Colab
Materials design Hybrid perovskites · ABX₃ Organic ion, metal and halide Minimise calculated electronic band gap Open In Colab
Microbial growth optimization BacPUS · Gut bacteria and polysaccharides Bacterial strain and polysaccharide Maximise mean growth at 48 hours Open In Colab
Enzyme inhibitor discovery Cyanimide library · Mouse USP18 Amine and carboxylic-acid building blocks Maximise mUSP18 inhibition Open In Colab
Drug combination optimization NCI-ALMANAC · Cancer cell assays Partner drug and two dose indices Minimise percent growth in a fixed cell-line context Open In Colab
Neural architecture search NAS-Bench-201 · CIFAR-10 Operations on six architecture edges Maximise validation accuracy for a fixed training seed Open In Colab
Software configuration tuning LLVM · Compiler flags Ten Boolean compiler options Minimise measured compilation time Open In Colab