Genetic Music System with Synthetic Biology (original) (raw)
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A Physiological Approach to DNA Music
2001
As a consequence of the Human Genome Project, there has been an explosion of primary DNA sequencing data available on the internet. Five years ago, we envisioned a type of computer-generated music that would take cues for its musical parameters directly from the physiological ones present in DNA. The first paper, Musical Synthesis of DNA Sequences, was presented and published at the Sixth International Symposium on Electronic Art, 1995 in Montreal; and XI Colloquio di Informatica Musicale, 1995 in Bologna. This updates our recent work.
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In the present work we present a methodology for teaching the basis of the genetic code through music composition, with the aim to combine science and arts learning. The project was carried out by 155 students, the so-called MARGA Consortium, with ages comprised between 10 and 17 years from different public schools located in the Principality of Asturias, Spain. The different groups generated 8 different music works using a short genetic sequence obtained from the human notch1 gene, receptor of mutations leading to chronic lymphocytic leukemia.
On Making Music with Artificial Life Models
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Our planet is a pulsating body inhabited by vibrating creatures and things. We are oscillatory beings resonating in a myriad of vibrating frequencies: both natural (brainwaves, heartbeat, ocean tides, and so forth) and artificial (telecommunications signals, radio, etc.). I am interested in the acoustics of the interplay between the artificial and the natural worlds, and in particular with the idea of composing music with the aid of a computer. To this end, I am investigating ways to make computational models of biological systems audible in order to make music with them. This paper introduces two systems of my own design, which uses cellular automata to compose music and synthesise sounds.
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We are investigating the potential of artificial life (Alife) models for composition and evolutionary musicology. This paper begins with a brief introduction to our research scenario and then revisits two systems of our own design that use cellular automata to control a sound synthesiser and to generate musical passages: Chaosynth and CAMUS. Next, we introduce a discussion on the potential and limitations of these two systems. Then, we present a new paradigm for Alife in music inspired by the notion of adaptive distributed-agent systems. We demonstrate how a small community of agents furnished with a voice synthesiser, a hearing system and a memory mechanism can evolve a shared repertoire of melodic patterns from scratch, after a period of spontaneous creation, adjustment and memory reinforcement. Keywords: Artificial life, cellular automata, evolutionary musicology, algorithmic composition, generative music, adaptive behaviour, collective machine learning.