I am a 4th year physics graduate student interested in any problem at the intersection of physics and biology. My research philosophy is "phenotypic modeling" (Paul Francois' term that I love). To me, this means researchers should start by finding interesting biological problems and then developing coarse-grained models of the system of interest. The models aren't designed to get all the microscopic details (genotype, etc) correct; instead the goal is to address only the microscopic details necessary to predict the macroscopic behavior (phenotype). The challenge (and my favorite part) in this research philosophy is finding the correct physics model for the problem. Often the needed physics necessary to develop the model exists but is disguised as a solution to another problem, while other times new physics techniques need to be developed.
With my research philosophy in mind, here are some biology problems I find fascinating (and hopefully will lead to future projects):
This is my existing physics toolkit (techniques I have used on projects), but I am always willing to expand this list :
See below for detailed explanations of my various research projects.
Our Work: Epigenetic landscapes explain partially reprogrammed cells and identify key reprogramming genes
The most exciting scientific experiment since 2006 was Takahashi and Yamanaka's reprogramming of a skin cell to something resembling an embryonic stem cell (ESC), dubbed induced pluripotent stem cells (iPSCs). Following this groundbreaking experiment, other reprogramming protocols have been found so now scientists can switch between a variety of cell types such as ESC, skin, liver, neurons, and cardiomyocytes (heart muscle). This has already revolutionized the understanding of biology and could change the future of medicine.
I am very interested in the answer to two different questions. First, what does it mean to be a cell type if minor perturbations (manipulate only a handful of transcription factors out of 1000's) can be performed to result in a completely different cell type? Second, how do we rationally design new reprogramming protocols? If we could make any desired cell type from an individual's own skin, this could eliminate the need for organ transplants.
So why am I, as a physicist, researching this? Well, biologists currently use Waddington's Landscape as an analogy to describe development and cellular reprogramming. As a physicist, the word landscape has a specific mathematical meaning, so my advisor Pankaj Mehta thought it would be a great first project for us to work together to see if we could make the analogy more precise. This project took off and now several years later, our model describes the biology much better than we had any right to expect.
We believe that, using our model, we can rationally design cellular reprogramming protocols. We were lucky to find an awesome group of experimentalists at the BU CReM. Darrell Kotton was intrigued enough by our model to have his graduate student Katie Benson test some of our reprogramming protocols. Experiments are ongoing (as of summer 2013) and hopefully positive results will follow soon!
Intrinsic noise of microRNA-regulated genes and the ceRNA hypothesis
By Javad Noorbakhsh, Alex H. Lang, and Pankaj Mehta
MicroRNAs are short sequences of RNA that can regulate gene expression by binding to mRNA. The ceRNA hypothesis recently proposed that microRNAs play an important role in gene regulation networks by inducing correlations between mRNAs that are competing for the same pool of microRNAs.
We mathematically modeled microRNAs by a set of stochastic differential equations. We found that microRNA networks are insensitive to many of the underlying biological details, but are responsive to the binding strength between the microRNA and mRNA. If the ceRNA hypothesis is true, all the microRNA and mRNA interaction rates need to be finely tuned to a similar value. Our work suggests that the ceRNA hypothesis is unlikely to play a major role in gene regulation, but specific microRNAs can play an important, albeit limited, role in regulation.
Flux balance analysis (FBA) is a technique to mathematical model metabolic networks. Daniel Segre and his group are developing software to implement FBA in spatial patterns. This will allow labs to investigate the interactions between various bacteria strains under multiple growing conditions and patterns, mimicking bacterial biofilms. We helped implement diffusion in this program.