graph-kernel-SVM-for-toxicity-of-pesticides-to-bees

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graph-kernel-SVM-for-toxicity-of-pesticides-to-bees

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reproduce our bee toxicity paper DOI: 10.1063/5.0090573

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### Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels

Python and Julia code to reproduce the results of our paper:
> P. Yang, A. Henle, X. Fern, C. Simon. Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels. _The Journal of Chemical Physics_. 2022. DOI: 10.1063/5.0090573. [link](https://aip.scitation.org/doi/10.1063/5.0090573)

:bee: the raw data from the [BeeTox AI project](https://www.sciencedirect.com/science/article/pii/S2667318521000131) is in the folder, `BeeToxAI Data/`.

:bee: the folder `/src` contains our source code for the random walk graph kernel.

:bee: to reproduce our results:
* run `python RDkit_smiles_convert.py` to convert the SMILES strings used in the BeeToxAI project into Daylight SMILES that can be parsed by `MolecularGraph.jl`.
* run `julia compute_Gram_matrices.jl` to pre-compute the Gram matrices, giving the L-RWGK between each pesticide molecule for different L.
* run `python fingerprint.py` to compute the MACCS fingerprints.
* open `kSVM_beetox.jl` in Pluto to train and evaluate the SVMs and produce the plots in the paper.

other scripts useful to us but likely not as useful to others:

:bee: the Julia scripts `test_run_time.jl` and `runtime_plot.jl` are to assess the run time.

:bee: open `toy_svm.jl` in Pluto to make a toy SVM visualization for talks.

:bee: `python viz_MACCS.py` makes visualizations of the molecules with substructures activating bits in the MACCS fingerprints.

:bee: open `viz_for_paper.jl` in Pluto to make visualizations of graphs we used to illustrate concepts in the paper.

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