About MERGE Project

Project Overview

The MERGE (Model Ensemble for Ranking Genomic Effect) framework is a cutting-edge pipeline designed for variant pathogenicity prediction. By avoiding reliance on clinical databases that cause "data circularity," MERGE utilizes a Dynamic Shunting Architecture to categorize variants into coding, non-coding, and splice regions.

The system integrates powerful foundation models, including Evo, HyenaDNA, Nucleotide Transformer, and AlphaGenome, ensuring robust performance across diverse genomic landscapes.

Command-line Tool (merge-cli)

We provide a professional CLI tool for high-throughput analysis. Officially published on PyPI, it supports complete offline execution and GPU-accelerated prediction.

# Install via pip
pip install merge-cli

The Research Team

Chen Yang
Lead Developer & Researcher
Medical Information Engineering, GZUCM
📧 chenyanggza01@163.com
Dr. Fang Li
Project Supervisor & Academic Mentor
Zhongshan School of Medicine, SYSU
📧 fangli9@mail.sysu.edu.cn