Author

M. Staller

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#protein folding Open access Sep 2026

Active learning enables evolutionary discovery and characterization of fungal transcriptional activators

Biological discovery and design are increasingly guided by predictive models trained on data from high-throughput technologies rather than costly experiments. However, existing datasets are often biased by overrepresentation of model organisms, causing models to fail in evolutionary studies of non-model species....

Lucas M. Waldburger, Hunter M. Nisonoff, Marissa A. Zintel et al. · Genome Biology · 0 citations

Review Open access Aug 2026

Interpretable biophysical neural networks of transcriptional activation domains separate roles of protein abundance and coactivator binding.

Deep neural networks have improved many difficult prediction tasks in biology, but it remains challenging to interpret these networks and learn the molecular mechanisms. Here, we address interpretation challenges by building biophysical neural networks for predicting activation domains, the regions within transcription...

Claire LeBlanc, Pooja Agarwal, Jack E. Demaray et al. · Cell Systems · 0 citations