Photo by Mike Bull
USC offers a new interdisciplinary beyond-the-classroom experience in music and biology
During the Spring 2018 term, students in DUDYCHA BIOL 599 Topics in Biology and BAIN MUSC 540/(737) (Advanced) Projects in Computer Music are teaming up in a unique beyond-the-classroom experience that focuses on student research/creative activity that lies at the intersections of evolutionary biology and algorithmic composition. It is part of the Mutational Music Project, the broader impact component of Dr. Jeff Dudycha’s National Science Foundation (NSF) grant Mutational variance of the transcriptome and the origins of phenotypic plasticity (NSF award #1556645). Dr. Reginald Bain is the other senior person on this grant.
Music enhances learning in STEM education
by Ellen Woodoff (from Da Capo 2015-16)
When biology professor Jeff Dudycha approached Reginald Bain, professor of composition and music theory, about collaborating on a National Science Foundation grant, Bain jumped at the prospect. “My previous experience in musical sonification and my deep interest in mathematics and computer science made this a very natural collaboration,” Bain said.
Genetic differences arise due to errors made when copying DNA, the molecule in which genetic information is stored. If the errors happen during cell divisions that lead to offspring, the differences will be inherited by future generations. Understanding these spontaneous mutations is a fundamental goal of biologists.
Bain, who directs the Experimental Music Studio at USC, is developing software that simulates genetic copying errors in the context of music. When students learn genetics, they often begin with misconceptions about mutations. But illustrating properties of mutations are difficult to show in class settings.
The software that will be developed under the Mutational Music project will be used as an interactive teaching tool that creates musical analogues of spontaneous mutations and more. Users will be able to create music by allowing an initial musical “seed” to mutate for a number of generations, and then compare the ancestral and descendent music aurally. The software will be based on established approaches to data sonification and computer music, and algorithms will be defined by information on the rate and characteristics of biological mutations.
Updated: January 20, 2018