Attentive FP with PyG #RDKit #PyG #pytorch_geometric #Chemoinformatics

As you know PyG is one of the useful package for graph based neural network as same as DGL-lifesci. Fortunately recent version of PyG is easy to install because it supports conda. So to install PyG, user don’t need to install related package such as pytorch_scatter, pytorch-cluster etc. etc. And PyG has lots of predefinedContinue reading “Attentive FP with PyG #RDKit #PyG #pytorch_geometric #Chemoinformatics”

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Run autodock-vina from ODDT #oddt #chemoinformatics #SBDD

I posted about auto_dock vina python bindings. It’s useful for python user because it can call autodock vina from python and run docking study on your python interprinter, jupyter notebook or script. I knew that ODDT (open drug discovery toolkit) supports virtual screening with vina and it has lots of useful method for drug discoveryContinue reading “Run autodock-vina from ODDT #oddt #chemoinformatics #SBDD”

Plot calibration curve with scikit-learn 1.0 #chemoinformatics #scikit-learn #memo

Recently scikit-learn ver. 1.0(nightly build) is released. I often use sklearn for my ask. So I would like to use new version ;) Current stable version is 0.24 so I installed 1.0.rc2 via pip. Here is a release Highlights and notes. https://scikit-learn.org/dev/auto_examples/release_highlights/plot_release_highlights_1_0_0.html https://scikit-learn.org/dev/whats_new/v1.0.html#changes-1-0 Ver 1.0 CalibrationDisplay method which can make calibration-curve plot easily. So IContinue reading “Plot calibration curve with scikit-learn 1.0 #chemoinformatics #scikit-learn #memo”

Try to use exmol to explain why the model predicts it #chemoinfomratics #RDKit #exmol

One of the difficult point of ML predictive model for chemoinformatics task is explainability of the model, why the model predicts these molecules the class. Especially if we use non liner model such as SVM, RF, NN, the problem is very important to have discussion with chemists because chemists would like to know that whyContinue reading “Try to use exmol to explain why the model predicts it #chemoinfomratics #RDKit #exmol”

Convert bit-vector to comma separated strings #memo #chemoinformatics #RDKit

Today’s post will be very short :) I had an MRI scan for my knee at the hospital today. It took almost 6 moths after my surgery. And the result was very well. So I could be able to running as same as before getting the surgery. I’m not young but I would like toContinue reading “Convert bit-vector to comma separated strings #memo #chemoinformatics #RDKit”

Probabilistic Random Forest approach to predict experimental value #RDKit #chemoinformatics #machine_learning

To build predictive model, input value(X) and target value(y) is required. But in the drug discovery area target value always has experimental error. So any experimental value (target value) may have uncertainly and it makes difficult to build predictive model. Recently Ola Engkvist group who is in AZ published interesting article in Jounral of chemoinformatics.Continue reading “Probabilistic Random Forest approach to predict experimental value #RDKit #chemoinformatics #machine_learning”

Run FMCS from C++ #RDKit #Chemoinformatics

I often write code with python because it has lots of useful packages, documents and community. And first programming language which I learned is python. So I’ve never wrote chemoinformatics code without python. But I have interested in coding with C++ / Rust because it works very fast. Today, I tried to wrote code withContinue reading “Run FMCS from C++ #RDKit #Chemoinformatics”

Cross docking study with python #Vina #Pymol #RDKit

I hope reader doing well and having nice weekend. Due to COVID-19 pandemic, our life is dramatically changed. I would like to go camp with my family when the pandemic is over. Last month, I wrote post about self docking (how to prepare input file and run vina from python) with vina-python API. Today IContinue reading “Cross docking study with python #Vina #Pymol #RDKit”