The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers
Abstract
:1. Introduction
2. Variants of Mutual Information Functions as Biomolecular Sequence Signatures
2.1. The Resolved Mutual Information Function Based on the Shannon Entropy
2.2. Rényi -Entropy and Related Mutual Information Functions
2.3. Tsallis -Entropy and Related Mutual Information Functions
3. Interpretable Classification Learning by Learning Vector Quantization
4. Applications of Mutual Information Functions for Sequence Classification
4.1. Data Sets
4.1.1. Quadruplex Detection
4.1.2. lncRNA vs. mRNA
4.1.3. COVID Types
4.2. Feature Generation
4.2.1. Natural Vectors
4.2.2. Mutual Information Functions
4.2.3. Handling of Ambiguous Characters
4.3. Classification
5. Results and Discussion
5.1. Classification Performance
5.2. Visualization of MIF Variants
5.3. Interpretation of CCM and CIP of the Trained LiRaM-LVQ Model
6. Conclusions, Remarks, and Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AMI | Average Mutual Information |
CCM | Classification Correlation Matrix |
CIP | Classification Influence Profile |
GISAID | Global Initiative on Sharing Avian Influenza Data |
GLVQ | Generalized Matrix Learning Vector Quantization |
IUPAC | International Union of Pure and Applied Chemistry |
lncRNA | Long Non-Coding RNA |
LiRaM-LVQ | Limited Rank Matrix Learning Vector Quantization |
LVQ | Learning Vector Quantization |
MIF | Mutual Information Function |
mRNA | messenger RNA |
NV | Natural Vectors |
rMIF | resolved Mutual Information Function |
RMIF | Rényi Mutual Information Function |
rRMIF | resolved Rényi Mutual Information Function |
rTMIF | resolved Tsallis Mutual Information Function |
SGDL | Stochastic Gradient Descent Learning |
TMIF | Tsallis Mutual Information Function |
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Data Set | Classes | Sequences | Per Class * | Mean Length | Std. Length |
---|---|---|---|---|---|
Quadruplex detection | 2 | 368 | 175/193 | 62.1 | 43.7 |
lncRNA vs. mRNA | 2 | 20,000 | 10,000 each | 1197.3 | 710.8 |
COVID types | 3 | 156 | 44/90/22 | 29,862.9 | 34.1 |
MIF | rMIF | |
---|---|---|
Shannon | ||
Rényi |
Data Set | NV | MIF | rMIF | ||
---|---|---|---|---|---|
Shannon | Rényi | Shannon | Rényi | ||
Quadruplex detection | |||||
lncRNA vs. mRNA | |||||
COVID types |
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Bohnsack, K.S.; Kaden, M.; Abel, J.; Saralajew, S.; Villmann, T. The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy 2021, 23, 1357. https://doi.org/10.3390/e23101357
Bohnsack KS, Kaden M, Abel J, Saralajew S, Villmann T. The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy. 2021; 23(10):1357. https://doi.org/10.3390/e23101357
Chicago/Turabian StyleBohnsack, Katrin Sophie, Marika Kaden, Julia Abel, Sascha Saralajew, and Thomas Villmann. 2021. "The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers" Entropy 23, no. 10: 1357. https://doi.org/10.3390/e23101357
APA StyleBohnsack, K. S., Kaden, M., Abel, J., Saralajew, S., & Villmann, T. (2021). The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy, 23(10), 1357. https://doi.org/10.3390/e23101357