網頁

2022年4月25日 星期一

紀錄

TUTORIAL TRAJ GROMACS: MDAnalysis no Jupyter Notebook

https://www.youtube.com/watch?v=RboD0i1EDdE

Practical Graph Neural Networks for Molecular Machine Learning

https://towardsdatascience.com/practical-graph-neural-networks-for-molecular-machine-learning-5e6dee7dc003

https://nbviewer.org/github/iwatobipen/playground/blob/master/gcn.ipynb

https://github.com/MolecularAI/GraphINVENT/tree/master/graphinvent/gnn

https://dmol.pub/dl/gnn.html#id89

https://github.com/gordicaleksa/pytorch-GAT

https://towardsdatascience.com/understanding-graph-convolutional-networks-for-node-classification-a2bfdb7aba7b

https://towardsdatascience.com/graph-convolutional-networks-on-node-classification-2b6bbec1d042

https://jonathan-hui.medium.com/graph-convolutional-networks-gcn-pooling-839184205692

https://colab.research.google.com/github/stellargraph/stellargraph/blob/master/demos/node-classification/gcn-node-classification.ipynb#scrollTo=Ni2iZB4MXMDQ

https://colab.research.google.com/github/stellargraph/stellargraph/blob/master/demos/node-classification/gat-node-classification.ipynb#scrollTo=eEWtLBYJYZto

https://github.com/stellargraph/stellargraph

https://colab.research.google.com/github/stellargraph/stellargraph/blob/develop/demos/interpretability/gat-node-link-importance.ipynb#scrollTo=26

https://github.com/danielegrattarola/keras-gat/tree/master/keras_gat

使用Molclus结合xtb做的动力学模拟对瑞德西韦(Remdesivir)做构象搜索

https://www.kryii.com/81.html

https://xtb-docs.readthedocs.io/en/latest/qcxms_doc/qcxms_run.html

https://colab.research.google.com/drive/18LqKvIW9iPi5BFI6yyEYtzn1czMOHeX2?usp=sharing#scrollTo=5WUBAQGicy0k

http://hyperparameter.space/blog/the-four-paths-to-molecular-machine-learning/

https://colab.research.google.com/drive/1YvQj-BDRKyk3UqbMvaqTu3pdq99kOx45#scrollTo=GhjNhwDbPJnz

https://github.com/qcxms/QCxMS

https://chemrxiv.org/engage/chemrxiv/article-details/613e83a7656369203b2a249b

https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/613e83a7656369203b2a249b/original/spec2mol-an-end-to-end-deep-learning-framework-for-translating-ms-ms-spectra-to-de-novo-molecules.pdf


liquid_time_constant_networks

https://github.com/raminmh/liquid_time_constant_networks/blob/a0bede1c742197f7db2f06dcabfcb7d6b58cfcdc/experiments_with_ltcs/har.py#L24


1D-MS_CumulativeLearningCNNs

https://github.com/KhawlaSeddiki/1D-MS_CumulativeLearningCNNs/blob/main/model_CNN.py

calc-ir-spectra-from-lammps

https://github.com/EfremBraun/calc-ir-spectra-from-lammps/blob/master/calc-ir-spectra.py

molxspec
https://github.com/dimenwarper/molxspec

Prediction of CO2 solubility in deep eutectic solvents using random forest model based on COSMO-RS-derived descriptors

https://www.sciencedirect.com/science/article/pii/S2666952821000534

https://nwchemgit.github.io/COSMO-Solvation-Model.html


4th-ML100Days

https://github.com/Halesu/4th-ML100Days