2019 Undergraduate Research Program
The Mathematical Biosciences Institute (MBI) is hosting a multi-institution REU program in the mathematical biosciences, facilitated by the Mathematical Biosciences Institute (MBI) located on the campus of The Ohio State University. The objectives of the program are: (1) to introduce a diverse cohort of undergraduate students to the mathematical biosciences, broadly interpreted to include areas such as biostatistics, bioinformatics, and computational biology, in addition to biologically-inspired mathematical modeling; (2) to encourage students to pursue graduate study in the mathematical biosciences; and (3) to increase the number of students who enter the workforce with training in this field.
REU participants work on projects in areas such as molecular evolution, neuronal oscillatory patterning, cancer genetics, epidemics and vaccination strategies, and animal movement. Participants work individually or in pairs under the guidance of expert mentors to make specific research contributions in these areas, often leading to a peer-reviewed publication and conference presentations. The REU program incorporates various professional and research-skills development activities throughout the summer to help ensure the participants’ success in completing their summer project and to prepare them for graduate study or entering the workforce.
The program consists of three parts:
- Mathematical Biosciences Bootcamp (June 10th-14th, 2019) at the MBI
At the MBI, participants are introduced to various areas of the mathematical biosciences via lectures and computer labs and visit various biological labs on campus.
- Mentored Research Experience (June 17th-August 2nd, 2019) at the REU host sites
During the second component of the program, participants complete a mentored research project individually or in pairs at one of MBI's partner institutions. Participants also attend a weekly online seminar series and virtual all-program meeting.
- Capstone Conference (August 5th-8th, 2019) at the MBI
For the final week of the program, the students return to the MBI to participate in the Capstone Conference. A student-centered conference featuring talks and posters by students doing research in mathematical biology, keynote talks by prominent mathematical biologists, a graduate studies recruitment fair, and other special features including a conference dinner and social event. Note that the Capstone Conference is open to all undergraduate students doing research in the mathematical biosciences, not only to students participating in the MBI REU.
To apply to our program, please go to www.nsfreu.org. The website will ask you to create a user account. When your account is created, follow the steps provided on the website to complete the common application. Make sure to select "MBI REU" when selecting the Sites to which you want to apply. The deadline for completing the application to our program is February 15th, 2019. If you have any questions about the application process, you may contact Will Gehring at firstname.lastname@example.org
Students accepted into the full program will receive room and board, a stipend, and a travel reimbursement allowance.
These project descriptions are subject to change and will be updated when new information is available.
REU Site: Indiana University – Purdue University Indianapolis (IUPUI)
Project 1 (Mentor: Dr. Jared Barber): Characterizing interactions between pairs of cells in tube/vessel flow: Blood is composed of mainly red blood cells (45%) and plasma. As blood flows through vessels, cells near walls are pushed towards the vessel center by wall interactions but pushed away from the vessel center by interactions with other cells. These competing effects have a primary role in how cells are distributed across the vessel which, in turn, affect distribution of other important quantities like oxygen. We have developed a two-dimensional computational model of red blood cell motion to use to consider how two isolated cells interact near vessel walls. The project, based on past work, will be to use the model to consider different types of interactions that pairs of cells undergo in this environment, how flexibility and vessel width affect the strength of these interactions, and the implications of such findings on red blood cell distribution across the vessel lumen.
Project 2 (Mentor: Dr. Julia Arciero): Modeling new therapies for heart transplantation: This project requires the design, analysis, and validation of a mathematical model of mouse heart transplantation and potential therapeutic approaches. Solid organ transplantation is a lifesaving procedure that requires lifelong immunosuppression to prevent organ rejection by the host immune system. While this treatment is necessary to protect the graft, it often leads to complications including hypertension, nephrotoxicity, cardiovascular disease, or chronic rejection. Thus, an improved treatment strategy is needed to promote long-term graft tolerance and health of the host. Regulatory T cells (Tregs) are a key component of the host immune system whose fundamental role is to inhibit the immune response. Thus, increasing host Treg levels through adoptive transfer has been proposed as an alternative strategy for promoting graft tolerance. The objective of this project is to adapt a previous ODE model of murine heart transplant rejection to include a dosing function simulating Treg adoptive transfer, the presence of immunosuppression, and an IL-2 population. When administering Tregs in isolation, Treg dose activation status, delivery site, magnitude, timing, and frequency are varied to maximize graft survival. Non-monotonic graft survival with respect to dose magnitude, timing, and frequency indicates that optimal dosing strategies must account for the dynamical interactions between the immune response and graft destruction. Since Treg delivery alone is not predicted to prevent eventual allograft rejection, combination strategies of adoptive transfer with immunosuppression and/or IL-2 administration will be determined in this work. These theoretical results will guide new investigations of combinatorial treatment strategies as well as in vivo experiments aimed at promoting graft tolerance.
Project 3 (Mentor: Dr. Jared Barber): Using a computational model to investigate breast cancer cell translocation: Breast cancer deaths are usually not due to the site of primary infection but rather by metastases at other locations. Preventing breast cancer cells from entering blood vessels (intravasation), traveling to other potential tumor sites (translocation), and migrating into the tissues at those sites (extravasation) could help mitigate the effects of cancer on the estimated 3.5 million people with a history of breast cancer. Experiments suggest that prevention of these metastatic events can depend on cell physical properties such as elastic and viscous coefficients as well as physical forces acting on the cells that can instigate mechanotransduction of cellular processes such as apoptosis, division, and others. To study these physical properties and forces, we have constructed a mechanical model of an individual cancer cell in a microfluidic device. The project is to investigate the numerical stability of our model by considering the numerical stability associated with a couple of simpler problems. Numerical stability corresponds with the step size one can take when running a simulation which corresponds with the overall speed with which one can produce a simulation. Understanding what parameters significantly affect the numerical stability of our model will help us as we calibrate and improve the current model so that we can use it to investigate how cell properties and mechanotransduced processes may contribute to the metastatic potential of breast cancer cells.
REU Site: New Jersey Institute of Technology (NJIT)
Project 1 (Mentors: Dr. Simon Garnier (NJIT), Dr. Jason Graham (U of Scranton)): Models of pattern formation and decision making in slime mold: In a complex and dynamic world, how do you navigate your environment when you do not possess a brain, or even the beginnings of a nervous system? From bacteria and immune cells to fungi and plants, the large majority of living beings face this problem every day. Nevertheless our knowledge of decision-making mechanisms is mostly limited to those of neuronal animals, and in particular vertebrates. The goal of this project is for students to explore with University of Scranton Associate Professor Jason Graham and NJIT Associate Professor Simon Garnier the navigational abilities of a non-neuronal model organism: the slime mold Physarum polycephalum. Using models of morphogenesis, the students will study (1) how external and internal stimuli modify the morphology of this giant cell as it moves through its environment and (2) how this morphological changes result in the integration of noisy and contradictory information during decision-making by P. polycephalum. The students will also compare their results to experimental data collected by Garnier’s lab as part of an IOS NSF-funded research effort. The results of this work will help understand information processing in organisms without a brain, thereby advancing our comprehension of the emergence of cognitive processes in biological systems.
Project 2 (Mentors: Dr. Anand U. Oza): Hydrodynamic interactions in animal schools and flocks: The complexity and beauty of fish schools and bird flocks have long fascinated scientists, as their complex collective dynamics are readily observed in nature. Recent experiments have suggested a hydrodynamic function for orderly formations in schools and flocks, but hydrodynamic interactions between fast-moving animals remain poorly understood. The goal of this project is for students to develop and analyze a mathematical model for schooling and flocking that accounts for the vortices shed by flapping wings. The model accounts for the temporally nonlocal hydrodynamic interactions between constituents, wherein the forces between bodies at a given time depend on their past positions and velocities. The project will combine mathematical analysis and computation to shed light on the role of hydrodynamics in stabilizing schooling formations, and the potential speed and energetic benefits of such formations.
Project 3 (Mentor: Dr. Enkeleida Lushi): Coupled dynamics of predator and prey plankton: Bdellovibrio bacteriovorus (BV) is a predator bacterial species found in the environment and within the human gut which preys and hunts other pathogen bacteria like Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Due to this remarkable ability, it is suggested that BV may serve as a biocontrol agent and a living antibiotic. We will explore a simple mathematical model of BV sensing and hunting pathogen bacteria with various shapes and surface attachment properties, to explore how BV proliferates whether it manages to eradicate a pathogen colony.
REU Site: The Ohio State University (OSU)
Project 1 (Mentor: Dr. Chuan Xue): Mathematical models for intracellular transport: A biological cell is like a city, and it has an internal transportation system that connects different parts of the cell. Nearly all cellular functions rely on the active transport of various cargoes, including proteins and organelles, inside the cell. Microtubules are long, dynamic polymers that serve as highway tracks for intracellular transport. Kinesin and dynein are motor proteins that move cargoes back and forth along microtubules. Disruptions of intracellular transport in nerve cells can cause local swelling of the axon, similar to a traffic jam that we see in real life, leading to nerve cell degeneration in severe situations. These phenomena have been found in many neurodegenerative diseases, such as ALS, Alzheimer’s and Parkinson’s. In this project, we will use mathematical models to investigate how intracellular traffic is regulated under normal conditions and how intracellular traffic jams arise under abnormal conditions. Sponsored in part by NSF CAREER Award 1553637.
Project 2 (Mentors: Dr. Oksana Chkrebtii, Dr. Amir Asiaeetaheri): Inference for generative models in biology and ecology: For many realistically complex models of in the mathematical biosciences, a likelihood function linking the model to the data cannot be written down explicitly. This project will study and implement techniques for fitting such models to data, when the model can be easily simulated under different regimes.
Project 3 (Mentors: Dr. Adrian Lam, Dr. Rachidi Salako): Phytoplankton Competition in Water Columns: Human activities have accelerated the eutrophication of many freshwater lakes and coastal ecosystems, including Lake Erie in the US and the Baltic Sea in Europe, causing harmful algal blooms (HABs) to emerge. This phenomenon can be explained by the competitive reversal between diatoms and cyanobacteria (or blue-green algae). Several ways of mitigating the phenomenon, involving physical mixing of the lake, has proved effective. In this project we will use a spatial model to study the competition dynamics among multiple phytoplankton species, to better understand HABs, and to weigh the cost and benefit of each mitigating method. This project will have a numerical component using Matlab programming, and an analysis component based on simplified models.
Project 4 (Mentors: Dr. Adrian Lam, Dr. Rachidi Salako): Spreading Phenomena of Interacting Species with Multiple Speeds: While the spreading of a single species in an unoccupied habitat is well understood, the question has been largely open in case of multiple species. The latter question has the potential to explain, for instance, the spreading of plant species in the de-glaciated North American continent after the last ice-age. In this project we will use the Lotka-Volterra model to study how multiple species spread into an empty habitat with multiple spreading speeds, and to recover the different speeds from model parameters. This project will have a numerical component using Matlab programming, and an analysis component based on simplified models.