Title:
Hypothesis-Driven Sonification of Proteomic Data Distributions Indicating Neurodegredation in Amyotrophic Lateral Sclerosis
Hypothesis-Driven Sonification of Proteomic Data Distributions Indicating Neurodegredation in Amyotrophic Lateral Sclerosis
Author(s)
Martens, William L.
Poronnik, Philip
Saunders, Darren
Poronnik, Philip
Saunders, Darren
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Abstract
Three alternative sonifications of proteomic data distributions were compared as a means to indicate the neuropathology associated with Amyotrophic Lateral Sclerosis (ALS) via auditory display (through exploration of the differentiation of induced pluripotent stem cell derived neurons). Pure visual displays of proteomic data often result in "visual overload" such that detailed or subtle data important to describe ALS neurodegradation may be glossed over, and so three competing approaches to the sonification of proteomic data were designed to capitalize upon human auditory capacities that complement the visual capacities engaged by more conventional graphic representations. The auditory displays resulting from hypothesis-driven design of three alternative
sonifications were evaluated by naïve listeners, who were instructed to listen for differences between the sonifications produce from proteomic data associated with three different types of cells. One of the sonifications was based upon the hypothesis that auditory sensitivity to regularities and irregularities in spatio-temporal patterns in the data could be heard through spatial distribution of sonification components. The design of a second sonification was based upon the hypothesis that variation in timbral components might create a distinguishable sound for each of three types of cells. A third sonification was based upon the hypothesis that redundant variation in both spatial and timbral components would be even more powerful as a means for identifying
spatio-temporal patterns in the dynamic, multidimensional data generated in current proteomic studies of ALS.
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2016-07
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Proceedings
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.