단백질시스템 연구실

• [12/28/2025] Global Joint Lab Partnership: Protein Systems Lab & Johns Hopkins University School of Medicine

• [12/30/2024] Overseas Research Training at Institute for Cell Engineering, Johns Hopkins University School of Medicine for Peptide Therapeutics Development in Parkinson's Disease 

• [02/19/2024] Featured Lab Introduction: Protein Systems Lab (formerly Proteomic Informatics Lab) on BRIC

• [11/10/2023] Featured Lab Introduction: Protein Systems Lab (formerly Proteomic Informatics Lab) on KOSEN

• [07/30/2023] Overseas Research Training at School of Chemistry and Chemical Engineering, University of Southampton: Development of Kinomics-Based Platform for Antibiotic Resistance Control

The research focus of the laboratory can be divided into three main areas:

1. Artificial Intelligence-powered Functional Protein Design

• Research on biomarker discovery through single-cellomics and multidimensional proteomics analysis: This area focuses on analyzing samples ranging from individual cells to complex tissues at high resolution. By utilizing single-cellomics and multidimensional proteomics technologies to collect data and combining this with network modeling, the research aims to identify and study disease-related biomarkers.

2. Biomarker Discovery through Single-Cell Proteome and Network Model

• Research on functional protein design through the integration of artificial intelligence and mass spectrometry technologies: This field combines cutting-edge AI algorithms with mass spectrometry techniques to rapidly design and validate therapeutic mini-proteins and peptides with enhanced stability and efficacy. The goal is to accelerate the development of innovative pharmaceuticals.

3. In Vitro & Companion Diagnostic LC-MS Assay in Clinical Laboratory

• Research on the development of in vitro diagnostics and companion diagnostics using mass spectrometry: This field leverages the superior sensitivity and specificity of mass spectrometers to develop disease detection methods that are faster and more accurate than existing approaches. Furthermore, through companion diagnostics research, the laboratory is paving the way for personalized medicine.

We are seeking passionate individuals who possess expertise in or are eager to learn the following fields:

• Biology (Engineering), Chemistry (Engineering), or related fields

Preference given to candidates with experience in bio-analytical instruments (such as liquid chromatography, mass spectrometry, flow cytometry, mass cytometry, etc.)

• Computer Science (Engineering), Bioinformatics, or related disciplines

Preference given to candidates with experience in programming languages (R, Python) and artificial intelligence/machine learning/deep learning

Prospective laboratory members (researchers, undergraduate students, graduate school applicants, and postdoctoral candidates) are encouraged to send their CVs via email to kimlab@cnu.ac.kr.