Multi-modal transformer for signal classification in nanopore blockade experiments

TL;DR - A multimodal transformer combines nanopore time series, wavelet images, and static features to classify molecular signals. It substantially improves peptide identification and could support robust, portable biomarker diagnostics.

• Outperforms prior methods by over 10 percentage points on a 42-peptide benchmark.
• Transfers to a 20-amino-acid dataset with near-perfect accuracy.
• Attention analysis indicates that time-series and wavelet inputs capture complementary signal characteristics.