Undergrads make strong showing at Mid-SURE Symposium
The Mid-Michigan Symposium for Undergraduate Research Experiences – or Mid-SURE for short – provides undergraduate researchers, visiting students participating in MSU summer research programs (such as the REU), and other students from select institutions with, “an opportunity for students involved in research and creative activities at Michigan State and select institutions to share their work with their peers, faculty, and external audiences.”
Mid-SURE 2016 took place on July 27 on the 4th floor of Spartan Stadium.
Following is a highlight of some of the participants and their research:
- Samuel Vaitkevicius, from the Brandizzi lab looked at a protein that is vital for an essential defensive mechanism used by plants and animals alike in the face of environmental stressors.
- Thien Crisanto ( visiting from Humboldt State University) and Daniel O'Hagan from the Ducat lab examined how to build and improve synthetic microbial communities that are driven by sunlight by using an organism that has lived for billions of years: cyanobacteria.
- Nicole Haddad (visiting from Purdue University) worked with the Howe lab on research demonstrating the importance of certain chemical compounds towards defending plants against herbivores.
- Ciara Fromwiller and Sean McGuire, from the Kerfeld lab, explored strategies to reengineer a protein structure, found in many bacteria, so it becomes a miniature factory that could create green energy or sustainably produce materials for use in biotechnology fields.
- Olivia Stephens (visiting from Spelman College), from the Montgomery lab, examined plant light receptors and how different parts of the light spectrum affect plant growth and development.
Researchers are integrating their work into undergraduate cell and molecular biology laboratory courses at Michigan State University through the use of Arabidopsis mutant screenings.
MSU-DOE Plant Research Laboratory (PRL) scientists have published a new study that furthers our understanding of how plants make membranes in chloroplasts, the photosynthesis powerhouse
A new AI system, called DeepLearnMOR, can identify organelles and classify hundreds of microscopy images in a matter of seconds and with an accuracy rate of over 97%. The study illustrates the potential of AI to significantly increase the scope, speed, and accuracy of screening tools in plant biology.