Diffusive Dynamics Analysis for Single-Molecule Tracking in Live Cells.
Robert Tjian, Professor
Molecular and Cell Biology
Closed. This professor is continuing with Spring 2024 apprentices on this project; no new apprentices needed for Fall 2024.
In live cells, biomolecules are in constant motion, driven by a range of specific and nonspecific interactions. These dynamic behaviors are key to understanding the in vivo properties and functional mechanisms of biomolecules. Single-molecule microscopes, which enable the tracking of individual target molecules, have opened new frontiers in this field. By analyzing the trajectories of these single molecules, we can gain critical insights into how they behave and function within the cellular environment.
Role: The selected undergraduate researcher is expected to learn and use state-of-the-art analysis techniques, starting from raw fluorescence microscopy data, through tracking, and culminating in the quantitative analysis of diffusive properties of target molecules. The student needs to learn, utilize and improve current data analysis methods for single-molecule tracking, as well as grasp the biophysical concepts underlying the quantitative analysis. This role will provide extensive experience in coding, data management, and statistical analysis. Additionally, the student will develop a deep understanding of the types of biophysical questions that can be addressed through single-molecule tracking.
Qualifications: The ideal candidate should have a foundational understanding of molecular biology and optical microscopy. Proficiency in Python programming and statistical inference is required, along with a solid knowledge of linear algebra and image processing. Familiarity with diffusion theory and Bayesian statistics is a plus. We are seeking a student who is collaborative, organized, committed, and eager to learn new skills. The student must also be prepared for the time commitment that research demands and be serious about contributing intellectually to single-molecule tracking data analysis. This position is open to undergraduates at all experience levels, with the possibility of increased independence based on experience and commitment. Preference may be given to students who can remain in the lab for more than one semester.
Day-to-day supervisor for this project: Ziyuan Chen, Post-Doc
Hours: 12 or more hours