Can We Use Physical Characteristics of Genes to Predict Age-Related Changes in Expression?
A Classifier-Based Exploration of Predictive Gene Properties
L. Mlikotić (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Gerard A. Bouland – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
I.C. den Hond – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
I.B. Pronk – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Marcel J.T. Reinders – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Kaitai Liang – Graduation committee member (TU Delft - Cyber Security)
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Abstract
The aim of this research is to investigate whether physical gene characteristics can predict age-related changes in gene expression. Specifically, we analyze gene length, GC content, distance to the ends of the chromosome, and similar features to determine their connection with differential expression between young and old individuals. Among these features, gene length consistently shows a strong correlation with age-related expression patterns. However, when combined, the selected features do not provide sufficient predictive power to train a classifier capable of exceeding a modest 66% accuracy. These findings highlight the limitations of the current feature set and point toward the need for more complex feature preprocessing steps or biologically relevant features in future predictive models.