sirpan Goto Github PK

disease-mesh-similarity

For each disease, a directed acyclic graph (DAG) is constructed based on hierarchical descriptors, in which nodes represent disease MeSH descriptors (or disease terms) and edges represent the relationship between the current node and its ancestors. Then compare the DAG Similarity.

gnnpapers

Must-read papers on graph neural networks (GNN)

hampdti

A heterogeneous graph automatic meta-path learning method for drug-target interaction prediction

ilearn

iLearn, a Python Toolkit and Web Server Integrating the Functionality of Feature Calculation, Extraction, Clustering, Feature Selection, Feature Normalization, Dimension Reduction and Model Construction for Classification, Best Model Selection, Ensemble Learning and Result Visualization for DNA, RNA and Protein Sequences.

kaggle_titanic_tutorial

kaggle_titanic_tutorial(data preprocessing, feature engineering, modeling)

parallel-sgd

Parallel implementation of Stochastic Gradient Descent using SciKit-Learn library in Python.

pyfeat

A Python-based Effective Feature Generation Tool from DNA, RNA, and Protein Sequences

scmfdd

sumgnn

This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)