Group members: Yusuf Omoson (Morehouse School of Medicine), German Enciso (UC Irvine), Ming Tan (UC Irvine), Scott Grieshaber
Originated: April, 2019
Description:
This working group is interested in using mathematical modeling to understand the association of microbial dynamics in the genital tract of female mice with Chlamydia infection. They will analyze sequencing data when it becomes available and plan to submit a manuscript. They would also like funding to continue the project and plan to submit a proposal.
CMCI participants presented 24 posters at the Science Expo on Friday. The poster session and lunch buffet are part of CMCI’s annual meetings with External Advisory Committee (EAC).
In addition to attending the poster session, EAC members Irene Eckstrand, Harmit Malik and Fred Adler met with project leaders, CMCI modeling fellows and staff, U of I executives and heard reports Collaboratorium leadership.
Afterwards, the EAC concluded:
We commend the U of I’s commitment to CMCI even as senior leadership at the university is changing. Like you, we believe that CMCI is the shape of the future, and we offer our continued support.
CMCI is one of many organizations on the U of I campus that offers research opportunities to undergraduate students. David Pfeiffer, Director of the Office of Undergraduate Research says:
“Why would you pick a career without taking it out for a spin? Whether a student wants to go into the hard sciences or the creative arts, we encourage all University of Idaho students to get real-world experience in their fields of study.”
Vandals in Focus is a magazine created by undergraduate students about undergraduate student research. And the 2019 edition has just been released.
College of Engineering assistant professor Min Xian earns funding toward portable detection device.
In Min Xian’s perfect world, the equipment needed for breast cancer detection will cost the medical community no more than what the average consumer pays for the latest and greatest iPhone. The University of Idaho College of Engineering assistant professor has been studying digital applications being developed to make breast cancer detection affordable and accessible. The latest technology uses a small scanning device that connects to your smart phone and uses algorithms and artificial intelligence to determine whether or not the scanned image is cancerous.
Under a $158,251 award from the Center for Modeling Complex Interactions, a multidisciplinary, collaborative research program housed at the U of I and funded by the National Institutes of Health, Xian has begun research into developing a more efficient algorithm for detection.
He also received a $12,570 award from the U of I Office of Research and Economic Development to purchase a portable scanning device to be used with the application.
“In developing countries, resources and access to medical doctors is limited,” said Min Xian, University of Idaho College of Engineering assistant professor. “They don’t have the techniques, and can’t afford the expenses.”
Applications like the ones Xian is studying would allow lesser trained individuals to provide the same level of medical expertise through an affordable and highly efficient form of artificial intelligence.
Although these applications currently exist, Xian said the technology still needs refinement, not to mention the time it will take to make the digital system acceptable to the public.
Breast cancer false positives cost the medical community greatly. Determining whether a tumor is malignant is difficult to do as a trained medical professional, so developing an artificial intelligence capable of limited error is no easy task.
His 19-person team consists of medical doctors and collaborators from the Utah School of Medicine, three other medical universities, two in China and one in India. The award will also fund a doctoral and one post-doctoral student.
“This kind of research isn’t done by a single person,” he said. “We need experts from a lot of different areas, not just computer science. We need medical doctors, we need statisticians.”
Group members: Darren Thompson, Tyler Siegford, Tanner Hahn
Originated: March 1, 2019
Description:
Modeling efforts of Muc7 homologs for understanding possible glycosylation patterning that will allow for bacterial agglutination. Using the preliminary results from this data we are attempting to synthesize the first of these analogs. We hope to see the first expected glycosylation models in September, as to create them synthetically and evaluate their viability.
