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bioinformatics, we developed models to predict the functional role that a given protein performs within a living organism. First, we trained neural networks, random forests, and support vector machines on proteins with known functions. Next, we submitted predictions on a set of over 130,000 proteins with unknown functions to CAFA (The Critical Assessment of protein Function Annotation algorithms), an international, competitive experiment, for assessment. Finally, we have developed a web application enabling

Adolescent Males Biomedical & Health Sciences1stZachary Song10OlympiaDegree of EpiPen Compression and its Effect on the Delivery Depth of Epinephrine to Prevent Fatalities from Anaphylaxis Biomedical & Health Sciences2ndRachel Daniel12BellarmineInvestigating Correlations Between Endometriosis and Bacteria Found in Peritoneal Fluid Biomedical & Health Sciences2ndXijie Jack Yu11Annie WrightScreening of potential biomarkers and key pathways in diabetic cardiomyopathy based on bioinformatics​ Biomedical

starts with an algorithm and then learns and adjusts on its own. Machine learning is an integral part of the modern technology world, used by companies such as Facebook and Google — and now, Renzhi Cao’s summer research at PLU. “We want to create a technique, where instead of telling the machine what to do, we want to give the intelligence to the machine,” Cao said. (Video by Rustin Dwyer, PLU) Cao and his team are working on applying machine learning to bioinformatics. They are writing an algorithm

Computer-Based Protein Modeling Biochemistry Lab Kasey Johnson, Senior Capstone Seminar Machine learning is a fast developing field with great promise into applications of bioinformatics. One of these applications is using machine learning to train models that can accurately choose best predicted models for protein fold predictions. Currently there is no laboratory exercise published that centers around using a machine learning based predictor for both understanding protein modeling as well as machine

business, you will likely be able to find interesting and challenging entry-level positions that seek people with strong quantitative skills. Your studies here can also prepare you for different graduate-level work including masters programs in mathematics, data science, and bioinformatics, that will prepare you for more advanced careers with major businesses or at national laboratories. Our graduates have paired their study of mathematics with majors such as Hispanic studies, English, or music and

from the last last 5 years: Their graduate programs Master of Science in Bioinformatics at Georgia Tech PhD in Plant Science, University of Arizona PhD in Evolutionary Development, University of Idaho PhD in Toxicology, North Carolina State University Dental School, University of Washington Pharmacy School, Washington State University Medical School, Boston University Master of Science in Genetic Counseling/Counselor, University of Minnesota PhD in Chemistry, University of Southern California