(2le) Complex Modeling in Biology: Studying Intracellular Entry in the Past and Aging in the Future

My goal is to establish a computational lab to advance our understanding of aging via realistic models grounded on experimental data. As a physicist who received a duo-mentorship from a biologist and an engineer, I am equipped with a unique perspective on engaging experimentalists to support this endeavor. My lab will implement software engineering to write reusable and AI-powered codes to promote the rapid development of realistic models, sustain effective collaborations with experimentalists, and make discoveries unreachable by either side alone. Here, I propose to study autophagy as my primary interest, which is one of the most important factors in aging. Autophagy is an intracellular process of degrading unnecessary or damaged components for reusing them as the building blocks for cellular repair or proliferation. Also meaning “self-eating”, autophagy is a crucial defense mechanism against aging and aging-related diseases. However, this wonder mechanism declines long-time-wise, which seems counterintuitive because aged cells contain more toxic targets than young cells that suppose to activate higher autophagic activity. Also, autophagy is complex short-time-wise, involving lipid transportation, membrane remodeling, and other mechanochemical processes. Uniting the governing mechanisms at these distinct time scales using realistic models to understand why autophagy declines in aged cells will be the major task for my lab.

Anti-aging is an ancient dream of humankind. Now, there is a better-than-ever chance to use the newest technologies in computations to pursue this old dream. I will be dedicated to carrying out the proposed research plan to make significant discoveries in this area by establishing a sustainable and fully funded research program on autophagy.

Specific aim

Aim1: To investigate the cause and biological purpose of declining autophagy in aged cells.

Aim2: To investigate the biophysical mechanisms of the formation of the spherical autophagosome (carrier of autophagic cargo).

Aim3: To build a software-engineering-based infrastructure and implement AI technologies in biophysical computations to rapidly develop realistic models.

Teaching Interests

I am dedicated to teaching courses related to computational biology. My goal is to combine traditional (blackboard and homework) classes and problem-based learning (PBL) classes to advance not only the knowledge learned but also the practical skills for solving real-world problems by the students. Through my teaching experience, I noticed students' tremendous learning efficiency boosted by PBL, which included high-level concentration, strong interaction, and deep interpretation. I will make efforts to incorporate PBL to enhance students' ability to solve non-textbook problems, practice teamwork, and find references. I believe these skills are vital for building their careers after graduation. In sum, my teaching interest is implementing PBL in computational biology education.