Single-Cell Genomics & AI Group (SCGA)

The Neurogenomics Lab at Kangwon National University is jointly led by Prof. Sehyun Chae and Prof. Jieun Kim. This site introduces the Single-Cell Genomics & AI Group (SCGA), our computational group led by Prof. Chae.

강원대학교 생물공학전공 채세현 교수 연구실 (단일세포 유전체·인공지능 연구그룹) 홈페이지에 오신 것을 환영합니다!

우리 연구실은 뇌와 면역계의 상호작용을 단일세포 수준에서 해석하는 연구를 수행하고 있습니다. 단일세포 전사체 및 공간전사체 분석 기술을 활용하여 개별 세포에서 유전자 발현을 측정하고, 이를 바탕으로 면역세포의 상태 변화가 뇌의 노화와 신경퇴행에 미치는 영향을 규명합니다. 나아가 단일세포·공간 유전자 발현 데이터와 다중오믹스 데이터를 통합적으로 분석할 수 있는 생물정보학 기법을 개발하고 있습니다.

또한 대규모 오믹스 데이터로부터 의미 있는 생물학적 정보를 추출하기 위해 인공지능(AI) 및 기계학습 기반의 분석 방법론을 개발하고 적용합니다. 세포의 상태와 상호작용, 그리고 질환과 연관된 변화를 데이터로부터 직접 학습하는 예측 모델을 구축함으로써, 새로운 생물학적 가설을 도출하고자 합니다.

이를 통해 뇌-면역 상호작용의 분자·세포 수준 기전을 데이터 기반으로 이해하고, 노화 및 신경퇴행성 질환에 대한 새로운 진단·치료 전략을 제시하고자 합니다.

Decoding neuro-immune crosstalk at single-cell resolution

Integrating single-cell, spatial, and multi-omics data with AI

Our group studies the interactions between the brain and the immune system at single-cell resolution. Using single-cell and spatial transcriptomics, we investigate how changes in immune cell states contribute to brain aging and neurodegeneration. In addition, we develop bioinformatics methods for the integrative analysis of single-cell, spatial, and multi-omics data.

We also develop and apply machine learning approaches to extract biological insights from large-scale omics data. By building predictive models that learn cellular states, interactions, and disease-associated changes directly from data, we aim to generate new biological hypotheses.

Through this approach, we seek to understand the molecular and cellular mechanisms of neuro-immune crosstalk, and to inform new diagnostic and therapeutic strategies for brain aging and neurodegenerative disease.

Research Topics

1. Heterogeneity and cell states of brain immune cells

We characterize the diversity of immune cells in the brain at single-cell resolution. By profiling microglia, border-associated macrophages, and peripheral immune cells, we define cell states associated with aging and neurodegenerative disease.

2. Spatial dissection of neuro-immune interactions

We examine how immune cells are organized within brain tissue and how they interact with neural cell types. By integrating spatial transcriptomics with intercellular signaling analysis, we map neuro-immune interactions across brain regions and cellular niches.

3. Immune mechanisms in brain aging and neurodegeneration

We track how immune cell states change during brain aging and disease progression. By relating these changes to neuroinflammatory processes, we identify molecular mechanisms and potential therapeutic targets.

4. Computational and AI-driven methods for omics data

We develop bioinformatics and machine learning approaches for integrating large-scale single-cell, spatial, and multi-omics data. By building models that learn cellular states and interactions directly from data, we generate testable biological hypotheses.

Research Areas: Single-cell and spatial genomics · Bioinformatics · AI and machine learning · Neuroimmunology

연구분야: 유전체학 · 생물정보학 · 인공지능 · 신경면역학