Semantically Rich Local Dataset Generation for Explainable AI in Genomics
Pedro Barbosa,
Rosina Savisaar,
Alcides Fonseca
Abstract:Black box deep learning models trained on genomic sequences excel at predicting the outcomes of different gene regulatory mechanisms. Therefore, interpreting these models may provide novel insights into the underlying biology, supporting downstream biomedical applications. Due to their complexity, interpretable surrogate models can only be built for local explanations (e.g., a single instance). However, accomplishing this requires generating a dataset in the neighborhood of the input, which must maintain synta… Show more
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