Association for Technology in Music Instruction National Conference (ATMI 2022)
Long Beach, CA

September 24, 2022

Teaching Algorithmic Composition through
Genetic Data Sonification

Reginald Bain, Professor
Composition and Theory
School of Music
University of South Carolina
813 Assembly St.
Columbia, SC 29208 USA


This paper presents pedagogical software that was created for a university-level introduction to computer music course and a semester-long interdisciplinary research experience for biologists and composers. The author uses Cycling ‘74’s Max, an interactive multimedia programming language and real-time composition environment, to create standalone software applications (apps) that allow students to explore basic principles of algorithmic composition in the context of data sonification and genetics. The apps and accompanying tutorials, which are freely available for download, provide students with multimedia learning spaces that guide them through the prerequisite music technology concepts, algorithmic approaches, and sonification techniques. This knowledge is required to execute the final project of the research experience, where groups of student biologists and composers are asked to represent basic processes of genetics and evolutionary biology (especially mutation) using musical processes.


Presentation Handout (pdf)

University of South Carolina Courses

MUSC 336 Introduction to Computer Music
Instructor: Reginald Bain
MWF 12:00-12:50 pm, Music Building, R006 and Computer Music Studio B, R011

MUSC 540/(737) (Advanced) Projects in Computer Music
Instructor: Reginald Bain
TBA, Music Building, Computer Music Studio B, R011

BIOL 599 Topics in Biology: Chords and Codons
Instructor: Jeff Dudycha (Professor, Department of Biological Sciences)
MW 2:20-3:35 pm, Coker Life Science Building, R202

Presentation Examples

  1. Getting Started with Max & MIDI
  2. Tutorial Example: Parameter-Mapping Sonification of Genetic Data using Max
  3. Research Resources

Mutational Music Project

This work is part of the the Mutational Music Project, an interdisciplinary project at the University of South Carolina that is focused on the development of music and software that helps students understand genetic mutation concepts. For more information, visit:

ATMI 2020 Presentation

For more information about the musical end of the interdisciplinary research experience, see my ATMI 2020 paper presentation Integrating Music and Genetics through Sonification and Data-Driven Music Composition:


Bain, Reginald. 2021. "Seed, from Double Helix." Proceedings of the 26th Annual International Conference on Auditory Display: 288-291. Available online at: <>.

____________. 2020. "Integrating Music and Genetics through Sonification and Data-Driven Music Composition." Association for Technology in Music Instruction national conference paper presentation. Available online at: <>.

Brooker, Robert J. 2009. Genetics: Analysis & Principles, 3rd ed. New York: McGraw Hill.

Burk, Phil, Larry Polansky, Douglas Repetto, Mary Roberts and Dan Rockmore. 2011. Music and Computers:  A Theoretical and Historical Approach, Archival Version. Available online at: <>.

Cycling '74. 2021. Max 8 Documentation. Available online at: <>.

Deamer, David. 1982. “Music: The Arts.” Omni Magazine (August 1982): 28 & 120.

Dobrian, Chris. 2017. Max Cookbook. Available online at: <>.

Dudycha, Jeffry L. 2018. “Introduction to Mutation.” BIOL 599 Topics in Biology: Chords and Codons. Unpublished course handout.

Dunn, John, and Mary Anne Clark. 1999. "Life Music: The Sonification of Proteins." Leonardo 32/1: 25–32.

Hass, Jeffery. 2021. Introduction to Computer Music: An Electronic Textbook, 2nd ed. Bloomington, IN: Indiana University. Available online at: <>.

Hayashi, Kenshi and Nobuo Munakata. 1984. "Basically musical." Nature 310 (July 12, 1984): 96.

Hermann, T., A. Hunt and J. G. Neuhoff, eds. 2011. The Sonification Handbook. Berlin: Logos Publishing House. Available online at: <>.

Hofstadter, Douglas. 1979. "Chapter 16. Self-Ref and Self-Rep." Gödel, Escher, Bach. New York: Basic Books.

Lodish, H., A. Berk; C. Kaiser; M. Krieger; M. P. Scott. 2008. Molecular Cell Biology, 6th ed. New York: W. H. Freeman.

Manzo, V.J. 2016. Max/MSP/Jitter for Music: A Practical Guide to Developing Interactive Music Systems for Education and More, 2nd ed. New York, Oxford.

Munakata, Nobuo and Kenshi Hayashi. 1995. "Gene Music; Tonal assignments of Bases and Amino Acids." In Clifford A. Pickover, ed., Visualizing Biological Information (1995): 72–83.

NCBI. 2016. Zika virus isolate Z1106033 polyprotein gene. Available online at: <>.

Purves, William K. and David E. Sadava. 2004. Life: The Science of Biology, 7th ed. New York: McMillian. New York: W. H. Freeman.

Nierhaus, Gerhard. 2009. Algorithmic Composition: Paradigms of Automated Music Generation. New York: Springer.

Takahashi, Rie and Jeffrey H. Miller. 2007. "Conversion of amino-acid sequence in proteins to classical music: search for auditory patterns." Genome Biology 8/5, Article 405 (2007).

Toussaint, Godfried. 2013. The Geometry of Musical Rhythm: What Makes a "Good" Rhythm Good?, 1st ed. Boca Raton, FL: CRC Press.

Tymoczko, Dmitri. 2011. A Geometry of Music: Harmony and Counterpoint in the Extended Common Practice. New York: Oxford University Press. {GB; Full text: Ebook Central}

Winkler, Todd. 1998. Composing Interactive Music: Techniques and Ideas Using Max. Cambridge, MA: MIT Press.

Wright, Matt. 2017. Programming Max: Structuring Interactive Software for Digital Arts. MOOC. Valencia, CA: Kadenze. Available online at: <>.


Special thanks to all of the students who participated in the Spring 2018, Spring 2020 and Spring 2022 interdisciplinary research experiences.

The investigators also wish to acknowledge the generous support of the University of South Carolina, Dean of the School of Music Tayloe Harding,  and Chair of the Department of Biological Sciences Johannes Stratmann.

The Mutational Music Project is the broader impact component of the National Science Foundation (NSF) grant project Mutational variance of the transcriptome and the origins of phenotypic plasticity (NSF award #1556645). Jeff Dudycha is the principal investigator and Reginald Bain is the other senior person on the grant.

Updated: September 21, 2022

Reginald Bain | University of South Carolina | School of Music