This thesis provides a physics account of the ability of cells to integrate environmental information to make complex decisions, a process commonly known as signaling. It strives to address the following questions: (i) How do cells relate the state of the environment (e.g. presence/absence of specific molecules) to a desired response such as gene expression? (ii) How can cells robustly transfer information? (iii) Is there a biophysical limit to a cells' ability to process information? (iv) Can we use the answers to the above questions to formulate biophysical principles that inform us about the evolution of signaling? Throughout, I borrow techniques from non-equilibrium statistical physics, statistical learning theory, information theory and information geometry to construct biophysical models capable of making quantitative experimental predictions. Finally, I address the connection of energy expenditure and biological efficiency by zeroing in on a process unique to eukaryotic cells-- nuclear transport. The thesis concludes with a discussion of our theory and its implications for synthetic biology.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/37062 |
| Date | 12 July 2019 |
| Creators | Wang, Chinghao |
| Contributors | Mehta, Pankaj |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Page generated in 0.0019 seconds