AdorableYoyo

CODE-AE

Coherent Deconfounding Autoencoder (CODE-AE) can extract both common biological signals shared by incoherent samples and private representations unique to each data set, transfer knowledge learned from cell line data to tissue data, and separate confounding factors from them

Data-Analytics

DeepCOP

DeepCOP - Deep Learning-Based Approach to Predict Gene Regulating Effects of Small Molecules

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

DGL_Classification

Drug_discovery_project_documentation

Karate_DGL_practice

MolGNN_fewshot

MultiDCP

TransPro

AdorableYoyo/CODE-AE

Coherent Deconfounding Autoencoder (CODE-AE) can extract both common biological signals shared by incoherent samples and private representations unique to each data set, transfer knowledge learned from cell line data to tissue data, and separate confounding factors from them

AdorableYoyo/Data-Analytics

AdorableYoyo/DeepCOP

DeepCOP - Deep Learning-Based Approach to Predict Gene Regulating Effects of Small Molecules

AdorableYoyo/dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

AdorableYoyo/DGL_Classification

AdorableYoyo/Drug_discovery_project_documentation

AdorableYoyo/Karate_DGL_practice

AdorableYoyo/Leetcode

AdorableYoyo/Molgnn

AdorableYoyo/MPL_DTI

AdorableYoyo/MultiDCP

MultiDCP: Predictive Modeling of Multiplex Chemical Phenomics for Novel Cells and Individual Patients: Application to Personalized Alzheimer’s Disease Drug Repurposing

AdorableYoyo/Neural-Networks-and-Deep-Learning

AdorableYoyo/NLP_final_project

AdorableYoyo/pretrain-gnns

Strategies for Pre-training Graph Neural Networks

AdorableYoyo/scGPT

AdorableYoyo/TransformerCPI

benchmark