Albi Celaj

Enigma is an efficient regulatory genomics model that achieves competitive performance with state-of-the-art models while significantly reducing computational cost.

FlashRNA improves computational efficiency for genomic sequence-to-function models while maintaining or enhancing predictive performance across multiple tasks.

This paper introduces REPRESS, a deep learning model that predicts cell-type-specific microRNA binding and mRNA degradation from RNA sequences, outperforming existing methods in multiple tasks.

The paper introduces BigRNA, an RNA foundation model that predicts RNA biology from DNA sequence and identifies therapeutic effects of SBOs on gene expression and splicing.

The paper introduces BFG-GI to map DNA damage-dependent genetic interactions in yeast by combining party mating and barcode fusion genetics, revealing new condition-specific interactions.