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Jiang Jing's Projects

anmf icon anmf

This is our implementation for the paper“Additional Neural Matrix Factorization model for Computational drug repositioning. BMC Bioinformatics ”

bert icon bert

TensorFlow code and pre-trained models for BERT

bert-loves-chemistry icon bert-loves-chemistry

bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.

code icon code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

d2l-mindspore icon d2l-mindspore

《动手学深度学习》的MindSpore实现。供MindSpore学习者配合李沐老师课程使用。

deepchem icon deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

dmol-book icon dmol-book

Deep learning for molecules and materials book

drug-repo icon drug-repo

A framework for computational drug repositioning

dti-mlcd icon dti-mlcd

Predicting drug-target interaction using multi-label learning with community detection method (DTI-MLCD)

edmot icon edmot

An implementation of "EdMot: An Edge Enhancement Approach for Motif-aware Community Detection" (KDD 2019)

graseq icon graseq

GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. In CIKM 2020.

intransformer icon intransformer

Data Augmentation-based Contrastive Learning by Injecting Noise into Transformer for Molecular Property Prediction

mat icon mat

The official implementation of the Molecule Attention Transformer.

meta-mgnn icon meta-mgnn

Few-Shot Graph Learning for Molecular Property Prediction

mgssl icon mgssl

Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"

molecule-attention-transformer icon molecule-attention-transformer

Pytorch reimplementation of Molecule Attention Transformer, which uses a transformer to tackle the graph-like structure of molecules

molt5 icon molt5

Associated Repository for "Translation between Molecules and Natural Language"

mpnn icon mpnn

Open source implementation of "Neural Message Passing for Quantum Chemistry"

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