Enhancing computational capability for quantitative and synthetic biology
Abstract
Abstract (for public release)A central goal of synthetic biology is to predictably engineer single cells and cell populations. These, engineered systems can elucidate the design principles underlying the operation of biological systems or lead to innovative applica,tions in biomanufacturing, materials engineering, and medicine. During this engineering process, mathematical modeling plays a criti,cal role in probing the design feasibility, guiding experimental design, or data interpretation. Each model can be mechanistic by de,scribing the key interactions entailed in each system, data-driven by exploiting machine learning techniques, or both. Likewise, mod,eling is also critical for developing a quantitative understanding of natural biological systems. In general, modeling is much more,efficient than the corresponding experiments. However, for certain applications, modeling can incur a prohibitive computational dema,nd, which diminishes its utility in guiding experimental design and optimization. Indeed, a number of our ongoing synthetic biolog,y projects, particularly the one on engineering pattern formation (supported by the Office of Naval Research), are now facing a trem,endous computational bottleneck, despite our use of the computer cluster provided by Duke University. To address this limitation, we, propose to request funds to purchase a set of computer servers with graphics processing units (GPUs). These new GPU servers will gr,eatly accelerate the computational component of the ongoing ONR project, as well as that of synthetic-biology or quantitative-biolog,y projects funded by other federal agencies. In addition to facilitating research, these instruments will augment the training exper,ience (in modeling and machine learning) of undergraduate students, graduate students, and postdocs participating in these research,projects in the You lab and at Duke.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 01, 2022
- Source ID
- N000142212320
Entities
People
- Lingchong You
Organizations
- Duke University
- Office of Naval Research
- United States Navy