Chaos Game Representation of Audio Signals

Cohen-McFarlane, Madison; Dick, Kevin; Green, James R.; Goubran, Rafik

doi:10.1109/i2mtc50364.2021.9459942

Cited by 1 publication

(1 citation statement)

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“…, (255, 255, 255)] where i ∈ [0, 255] is an integer encoding the relative subsequence frequency. In prior work, we show that this additional encoded information at times leads to improved predictive performance [10] and can additionally be extened to new domains such as for audio signal representation [11].…”

Section: The Chaos Game Representationmentioning

confidence: 92%

Can a Sparse 2⁹× 2⁹Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

Dick

Green

2023

Preprint

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No. While our experiments ultimately failed, this work was motivated by the seemingly reasonable hypothesis that encoding protein sequences as a fractal-based image in combination with a binary mask identifying those pixels representative of the protein binding interface could effectively be used to fine-tune a semantic segmentation model. We were wrong. Despite the shortcomings of this work, a number of insights were drawn, inspiring discussion about how this fractal-based space may be exploited to generate effective protein binding site predictors in the future. Furthermore, these realizations promise to orient complimentary studies leveraging fractal-based representations, whether in the field of bioinformatics, or more broadly within disparate fields leveraging sequence-type data, such as Natural Language Processing. In a non-traditional way, this work presents the experimental design undertaken and interleaves various insights and limitations. It is the hope of this work that those interested in leveraging fractal-based representations and deep learning architectures as part of their work will benefit from the insights arising from this work.

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Section: The Chaos Game Representationmentioning

confidence: 92%

Can a Sparse 2⁹× 2⁹Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

Dick

Green

2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Chaos Game Representation of Audio Signals

Cited by 1 publication

References 20 publications

Can a Sparse 2⁹× 2⁹Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

Can a Sparse 2⁹× 2⁹Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

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Chaos Game Representation of Audio Signals

Cited by 1 publication

References 20 publications

Can a Sparse 29× 29Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

Can a Sparse 29× 29Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

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Can a Sparse 2⁹× 2⁹Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?

Can a Sparse 2⁹× 2⁹Pixel Chaos Game Representation Predict Protein Binding Sites using Fine-Tuned State-of-the-Art Deep Learning Semantic Segmentation Models?