A New Deep Learning and XAI-Based Algorithm for Features Selection in Genomics

Carlo Adornetto, Gianluigi Greco
3/29/2023
q-bio.GNcs.AIcs.LG

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Abstract

In the field of functional genomics, the analysis of gene expression profiles through Machine and Deep Learning is increasingly providing meaningful insight into a number of diseases. The paper proposes a novel algorithm to perform Feature Selection on genomic-scale data, which exploits the reconstruction capabilities of autoencoders and an ad-hoc defined Explainable Artificial Intelligence-based score in order to select the most informative genes for diagnosis, prognosis, and precision medicine. Results of the application on a Chronic Lymphocytic Leukemia dataset evidence the effectiveness of the algorithm, by identifying and suggesting a set of meaningful genes for further medical investigation.

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Cite this paper

@article{adornetto2023deep,
  title  = {A New Deep Learning and XAI-Based Algorithm for Features Selection in Genomics},
  author = {Carlo Adornetto and Gianluigi Greco},
  year   = {2023},
  eprint = {2303.16914},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.16914v1}
}

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