Emaad Khwaja

CELL-E 2 translates protein sequences to images of subcellular localization and vice versa, enabling de novo protein design and generating novel nuclear localization signals.

CELL-E generates 2D probability density maps of protein localization using text-to-image transformers, avoiding discrete class annotations.

This work improves fluorescence microscopy image denoising by combining self-supervised and transfer learning to reduce the need for task-specific training data.