Research Projects

This is a list of research projects that may have opportunities for undergraduate students. You can browse all the projects, or view only projects in the following categories:

Life Science

 

Characterization of Stomatal Development Genes

Research categories:  Agricultural, Bioscience/Biomedical, Environmental Science, Life Science
School/Dept.: Horticulture
Professor: Mike Mickelbart
Preferred major(s): Biology, biochemistry, or related majors
Desired experience:   Biology and genetics
Number of positions: 1

Stomata are small pores on the surface of leaves that regulate gas exchange with the environment. The genetic determinants of stomatal density (SD) changes in response to intrinsic or extrinsic factors are largely unknown. We screened a large population of Arabidopsis thaliana and identified genetic regions correlated with differences in stomatal density. Within these genetic regions, we have selected candidate genes that may be involved in stomatal development. The goal of this summer project is to utilize plants that have mutations in genes of interest to determine if they affect stomatal development. Natural genetic variation will also be used to assess differences in expression of these genes in a diverse set of plant material. The student will gain experience in DNA and RNA isolation, gene expression, DNA sequencing, growth measurements, and leaf anatomical characterization using light microscopy.

 

Constructing Large Scale Representative Social Networks

Research categories:  Bioscience/Biomedical, Computational/Mathematical, Computer Engineering and Computer Science, Educational Research/Social Science, Industrial Engineering, Life Science, Physical Science
School/Dept.: Industrial Engineering
Professor: Mario Ventresca
Desired experience:   At least one student with object-oriented programming, data structures, algorithm analysis, as well as familiarity with at least basic discrete mathematics, statistics and probability (graph theory, distributions, hypothesis testing, regression, etc). Experience using MPI/parallel computation would be highly advantageous, but not necessary. Familiarity with Linux and R would also be useful. A student with a background in epidemiology or applied mathematics would also be very strongly considered.
Number of positions: 1-2

Facebook, Twitter, Orkut and LinkedIn are well known examples of cyber-social networks. However, social networks obviously exist outside of that domain and can represent the connections we make with the people around us. Unlike cyber-world social networks where the connections people make are fully known and observable, real-world networks must be inferred from limited statistical information as well as reasonable assumptions about human behavior. In both instances, a representative social network allows for the study of not only the network topological properties but also diffusive processes acting upon it, such as information spread, influence, disease, etc. There exists a gap in our ability to reconstruct real-world networks from partially observed, noisy and limited data.

This project will aid in developing efficient and scalable algorithms for constructing real-world social network representations at different scales and abstractions (up to global). An extensive literature review of existing capabilities and known social behaviors/mixing patterns will be conducted as part of the project, as will data acquisition and analysis.

 

Effects of climate change and nitrogen on woody plants and tallgrass prairie

Research categories:  Environmental Science, Life Science
School/Dept.: Forestry and Natural Resources; Biological Sciences
Professor: Jeff Dukes
Preferred major(s): Biology, Forestry, Environmental Science, Earth, Atmospheric, and Planetary Science, Environmental Engineering
Desired experience:   A knowledge of basic plant biology is desired, but not required.
Number of positions: 1

The Prairie Invasion and Climate Experiment (PRICLE) examines the effects of two global change factors, nitrogen fertilization and climate change, on plant community composition and ecosystem processes in tallgrass prairie. Particularly, PRICLE considers how more variable rainfall might interact with nitrogen addition to influence the spread of invasive or weedy plant species. Since its start in 2012, PRICLE has focused on grasses and wildflowers, but starting in 2014, the experiment will be expanded to include tree and shrub species. Students working on PRICLE will be tasked with collecting data on tree growth and prairie community composition in the field, as well as processing and analyzing materials in the lab. Over the course of the summer, students will conduct in-field measurements of plant growth and community composition, assist in the application of experimental treatments, and conduct elemental analyses of plant tissues and soils. Students will also be encouraged to design their own project within the larger experimental design.

While working on PRICLE, students will learn a suite of techniques relevant to in-field environmental measurements and in-lab analyses, and gain valuable experience in field ecology. PRICLE has hosted SURF students twice before (in 2012 and 2013), and students will work closely with the same Ph.D. candidate this year as in years past. Students working on PRICLE should expect to spend at least one day per week on average conducting research in the field, with remaining time spent conducting research in the lab.

 

Modeling Metabolic Flux for Bioenergy

Research categories:  Agricultural, Life Science
School/Dept.: Department of Biochemistry
Professor: Clint Chapple
Preferred major(s): biochemistry, plant genetics, chemical engineering or related area
Desired experience:   Biochemistry of metabolism
Number of positions: 3

The sun is the principle source of energy for our planet, and photosynthesis is the primary mechanism by which that energy is captured and stored in the form of reduced carbon. An outcome of these biochemical events is that plants represent a quantitatively important, sustainable, and carbon-neutral source of energy for humans. In order to maximize the utility of plants for this purpose, it is critical that we gain control of the processes associated with energy capture and storage, including the molecular mechanisms that allocate fixed carbon to the myriad biochemical pathways in plants, including the shikimate and phenylpropanoid pathways that together contribute to the biosynthesis of lignin, a polymer that comprises approximately 25% of plants’ biomass.

In this project, a student will work with graduate students and post docs to develop a kinetic model for the shikimate and phenylpropanoid pathways. Kinetic models provide insights into the distribution of flux control, thus permitting more intelligent, predictive and effective design of experiments to modulate fluxes towards pathway end products. The anticipated outcomes from our proposed kinetic modeling are two-fold: first, it identifies what remains unknown about the regulation and control of metabolic fluxes to lignin; second, the model allows development of strategies and predictions of what targets are the most promising candidates for alteration of metabolic flux to lignin. This meets the desired goal of designing modules for precise control of metabolic pathways in plants.

Other Purdue faculty members involved with this project are Dr. Natalia Doudareva and Dr. John Morgan.

 

Optimization of antibody penetration for 3D tissue imaging

Research categories:  Bioscience/Biomedical, Innovative Technology/Design, Life Science
School/Dept.: Biomedical Engineering
Professor: Sarah Calve
Preferred major(s): BME/Biology
Number of positions: 1

Recent advances in tissue clearing have increased the depths to which conventional confocal microscopy can image by at least an order of magnitude. Unfortunately, researchers are limited by the ability to only image endogenous fluorescence as passive diffusion of antibodies into intact tissues, to specifically label molecules of interest, can take weeks. Our lab is developing a method to actively promote the diffusion of primary and secondary antibodies into biological tissues to better take advantage of these new clearing techniques.

We are looking for a student to help optimize this method to better label key extracellular matrices expressed during tendon and muscle development in the mouse. The student will be directly involved in harvesting embryos from mice in which the muscle or tendon progenitors endogenously express green fluorescent protein, optimizing the active antibody staining protocol being developed in our lab and imaging the specimens using confocal microscopy. The overall goal of this research is to characterize the 3D composition of the extracellular environment during muscle and tendon assembly inform the design of artificial scaffolds to promote tissue regeneration.