Data-Driven Insights: Deep Learning Revolutionises Separation in Proteomics
Lector: doc. RNDr. Jiří Urban, Ph.D.
Institution: Masaryk University, Faculty of Science
Field: Analytical Chemistry
About the project
Most diseases are manifested at the protein level. Liquid chromatography coupled with mass spectrometry is the core method for their identification. This project aims to enhance the method's performance by developing a universal chromatographic prediction model using deep learning protocols. With this approach, the contribution of analyte properties to its retention will be comprehensively described, leading to higher precision in protein identifications and application in clinical proteomics.
Why science?
Science is highly intellectually stimulating and enhances critical thinking, independence, and problem-solving skills. My scientific endeavours are rooted in a deep desire to make a tangible, positive impact.
What do I like most about Brno
Brno houses reputable research institutions and universities. I appreciate its vibrant research community and the possibility of working on state-of-the-art technologies.