Mass Spectrometry
Our Mass Spectrometry (MS) research focuses on advancing both experimental and computational approaches to unravel the complexities of protein structure and function. By combining innovative labeling techniques with state-of-the-art data analysis methodologies, we aim to push the boundaries of proteomics and structural biology.
Our research is at the forefront of Mass Spectrometry innovation, bridging experimental breakthroughs and computational advancements to deliver transformative insights into the molecular machinery of life.
Key Areas of Research:
Development of Novel Labeling Methods for Protein Structure Determination
- Designing cutting-edge chemical and isotopic labeling strategies to enhance the resolution and accuracy of protein structure determination.
- Exploring site-specific labeling techniques to map protein-protein interactions, conformational changes, and dynamic modifications.
Advanced Computational Methods for Mass Spectrometry Data Analysis
- Creating algorithms and software tools to process, interpret, and visualize MS data with high accuracy and speed.
- Developing machine learning models for peak identification, quantification, and classification to enhance proteome-wide studies.
- Integrating multi-omics data, such as MS-based proteomics with transcriptomics and metabolomics, for a holistic understanding of biological systems.
Applications in Structural Proteomics and Beyond
- Applying MS-driven approaches to investigate protein folding, post-translational modifications, and interaction networks.
- Facilitating drug discovery and biomarker identification by uncovering structure-function relationships in therapeutic targets.
- Supporting dynamic studies to monitor changes in protein structure and function under different physiological and pathological conditions.