Jo Lab

Research Tools

Deep learning platforms and open-source tools developed by Jo Lab

Web Platforms

DuAL-Net

Dual Approach Local-global Network

Hybrid framework combining local and global genomic features for Alzheimer's disease prediction from whole-genome sequencing data.

Launch Result Preview Paper (in press)

TrUE-Net

Transformer Uncertainty Ensemble

Uncertainty-aware genomic deep learning framework using transformer ensembles for Alzheimer's disease classification.

SWAT-web

Sliding Window Association Test

Genome-wide sliding window association analysis of whole-genome sequencing data using deep learning.

Open Source & Resources

AlphaGenome MCP

MCP server enabling natural language interaction with genomic deep learning models for Alzheimer's disease research.

GitHub →

Deep-Block

Deep learning framework for block-wise genomic analysis, used in LD-informed variant detection from WGS data.

GitHub →

SWAT

Command-line implementation of the Sliding Window Association Test for genomic data analysis.

GitHub →

c-SWAT

Circular SWAT variant for deep learning-based diagnostic classification using metabolomics data.

GitHub →

VibeIndex

Real-time directory that indexes and ranks AI coding tools, skills, and MCP servers with automated security scanning.

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JoLab GitHub

All open-source repositories, code, and research tools from Jo Lab.

GitHub →