From 37190c1ff790a59c80b129b69f069233cf015f78 Mon Sep 17 00:00:00 2001 From: Alejandro Velez-Arce Date: Tue, 3 Sep 2024 16:35:37 -0400 Subject: [PATCH] mend --- single_pred_tasks/MPC/index.html | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/single_pred_tasks/MPC/index.html b/single_pred_tasks/MPC/index.html index 1136959f..b7593bd1 100644 --- a/single_pred_tasks/MPC/index.html +++ b/single_pred_tasks/MPC/index.html @@ -292,20 +292,22 @@

Wan Xiang et al.

Dataset Split: Random Split Scaffold Split 

from tdc.single_pred import MPC
-data = MPC(name = "INSERT_URL_HERE" # url from the source github repo https://github.com/bidd-group/MPCD/tree/main/dataset
+data = MPC(name = "INSERT_URL_HERE") # url from the source github repo https://github.com/bidd-group/MPCD/tree/main/dataset
+# example url: https://github.com/bidd-group/MPCD/blob/main/dataset/ADMET/DeepDelta_benchmark/Caco2.csv 
 split = data.get_data()
-

We additionally support direct retrieval from the MoleculeACE API for those datasets. You can call:

+

We additionally support direct retrieval from the MoleculeACE API [2] for those datasets. You can call: 


-data = MPC(name = "INSERT_MOLECULEACE_HERE", get_from_gh = False # name from MoleculeACE API https://github.com/molML/MoleculeACE?tab=readme-ov-file
+data = MPC(name = "INSERT_MOLECULEACE_HERE", get_from_gh = False) # name from MoleculeACE API https://github.com/molML/MoleculeACE?tab=readme-ov-file

References:

[1] Wan Xiang, et al. “Online triplet contrastive learning enables efficient cliff awareness in molecular activity prediction” 28 June 2023, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-2988283/v1].

+

[2] van Tilborg et al. "Exposing the Limitations of Molecular Machine Learning with Activity Cliffs.", Journal of Chemical Information and Modeling, 2022, 62 (23), 5938-5951. DOI: 10.1021/acs.jcim.2c01073.

Dataset License: CC BY 4.0.