DARSI Predicts Gene Expression And Binding Sites
Karshenas, Röschinger and Garcia publish DARSI on April 1, 2026 in PLoS Computational Biology, introducing a convolutional neural network that predicts gene expression from raw regulatory DNA using MPRA training data. The model localizes transcription factor binding sites at single-base resolution, validates predictions against curated databases, and releases code and trained models on GitHub to enable experimental follow-up.
Scoring Rationale
Peer-reviewed PLoS Computational Biology paper introducing a novel CNN (DARSI) trained on MPRA datasets with validated, single-base binding-site localization and public code, boosting novelty, credibility, actionability, and relevance. Scope is focused on regulatory genomics rather than industry-wide impact, which lowered the scope score slightly; published today, so no freshness penalty applied.
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Sources
- Read OriginalPredictive modeling of gene expression and localization of DNA binding site using deep convolutional neural networksjournals.plos.org
