SMFS
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Related Articles from SNS
Automating the Expert Eye: A System-Agnostic Deep Learning Framework for Rare Event Discovery in Imbalanced Force Spectroscopy
arXiv:2606.09541v1 Announce Type: new Abstract: Single-Molecule Force Spectroscopy (SMFS) provides unprecedented insights into biomolecular mechanics, yet the high-throughput generation of force-extension trajectories creates a severe data curation bottleneck. Identifying rare molecular unbinding events within thousands of noise-dominated curves traditionally relies on tedious, non-scalable manual auditing. Here, we present a system-agnostic, interpretable deep learning framework tailored to...
Automating the Expert Eye: A System-Agnostic Deep Learning Framework for Rare Event Discovery in Imbalanced Force Spectroscopy
arXiv:2606.09541v1 Announce Type: cross Abstract: Single-Molecule Force Spectroscopy (SMFS) provides unprecedented insights into biomolecular mechanics, yet the high-throughput generation of force-extension trajectories creates a severe data curation bottleneck. Identifying rare molecular unbinding events within thousands of noise-dominated curves traditionally relies on tedious, non-scalable manual auditing. Here, we present a system-agnostic, interpretable deep learning framework tailored...
Accounting for recurrent mutation in the frequency spectrum of rare alleles
As whole-genome and whole-exome datasets increase in size, they uncover alleles at lower and lower frequencies in the population. Samples of rare alleles often include recurrent mutations, where derived alleles are identical by state and not by descent. As a result, the site frequency spectrum (SFS) becomes challenging to analyze because it is strongly dependent on the mutation rate.