Research Focus
Computational, statistical, and artificial intelligence approaches for integrating genomic, transcriptomic, and other multi-omics data with large-scale multi-modal real-world data (RWD) to advance disease discovery, diagnosis, and precision medicine.
Research Overview
The Jeong Lab develops computational, statistical, and artificial intelligence approaches to understand and diagnose human disease. Building on expertise in computer science, transcriptomics, and next-generation sequencing-based genomics, the lab creates scalable algorithms and software platforms that transform large-scale biomedical data into biological and clinical insight.
The lab's work spans CRISPR screen analysis, transposable element quantification, multi-omics integration, electronic health record analysis, and rare disease gene prioritization. Current efforts are expanding into biomedical artificial intelligence, including diagnostic foundation models, multimodal AI, and language-aware systems that integrate molecular profiles, clinical phenotypes, electronic health records, real-world data, and biomedical knowledge.
Through tools such as CRISPRcloud, SalmonTE, LA-MARRVEL, and MARRVEL-MCP, the lab aims to build robust, interpretable, and clinically useful systems that support precision medicine and accelerate discovery across rare disease, neurological disease, and human health.
Key Tools / Software
MARRVEL-MCP
Natural-language query interface for Mendelian disease discovery via MCP.
AI-MARRVEL
AI system for automated rare genetic disease diagnosis.
CRISPRcloud2
Cloud-based platform for CRISPR pooled screen deconvolution.
CB2
R package for CRISPR pooled screen analysis.
SalmonTE
Ultra-fast quantification of transposable element abundances from NGS data.
TraceQC
R package for QC of CRISPR lineage tracing sequence data.