NYXFLOWER

TIP

TIP: Tri-graph Interaction Propagation model for Polypharmacy Side Effect Prediction (GRL@NeurIPS, 2019)

GripNet

GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs (PatternRecognit, 2023)

APRILE

APRILE: A python library for exploring Adverse Polypharmacy Reaction using Intelligent Learner and Explainer

APRILE-Exp

This is the repository for reproducing results in "APRILE: Exploring the Molecular Mechanisms of Drug Side Effects with Explainable Graph Neural Networks".

UPSR

Predicting the enzymatic functions of protein structures

APRILE-Pred

PoSe-Model: A simplified TIP model for drug side effect prediction (Under development...)

DrugDiscovery

An explainable inductive learning model on gene regulatory and toxicogenomic knowledge graph (under development...)

AlgorithmStudy

APRILE-CaseStudies

Bio-Chem-Graph-Representation-Learning

Biofilm

analysing and visualising biofilm simulation results from GEMs with unsupervised methods

cse282-nutriomics-project

Solving combinatorial selection of nutrients to treat patients with low abundance microbes

DeCA

DeepPurpose

A Drug-Target Interaction Prediction Toolkit with State-of-the-Art Deep Learning Methods and its Applications in Drug Repurposing and Virtual Screening

denovopipeline

Pipeline for de novo peptide sequencing (Novor, DeepNovo, SMSNet, PointNovo, Casanovo) and assembly with ALPS.

drug-repurposing-leishmaniasis

This is the sub working repository for "Compound Screening with Deep Learning for NeglectedDiseases: Leishmaniasis." (MLCB, 2021)

drug-repurposing-leishmaniasis-1

GCNII

PyTorch implementation of "Simple and Deep Graph Convolutional Networks"

gnn-model-explainer

gnn explainer

google-research

Google Research

MeMo

Constraint-based metabolic modelling with sparse IPOPT

MetaSE-ML

A pipeline for predicting drug response via a novel tensor-contraction based ML model and GEM simulations

nyxflower

A personal research repository for fun

ogb

Benchmark datasets, data loaders, and evaluators for graph machine learning

prosit

Prosit offers high quality MS2 predicted spectra for any organism and protease as well as iRT prediction. When using Prosit is helpful for your research, please cite "Gessulat, Schmidt et al. 2019" DOI 10.1038/s41592-019-0426-7

prosittransformer

on predictions of ms2-spectra

py3pdb

Benchmark datasets, data loaders and evaluators for protein function and property prediction

pykale

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem

tape

workflow_dev