Sarah Alamdari

FLIP2 adds seven protein fitness datasets and 16 splits for enzymes, light-sensitive proteins, and interactions; simple ridge and zero-shot baselines often rival fine-tuned protein language models.

CleaveNet is an AI pipeline that designs protease substrates with high efficiency and selectivity, validated experimentally for MMP13.

The paper introduces the Dayhoff Atlas, a resource with large protein sequence datasets and generative models to improve protein design and prediction.

ProtNote is a multimodal deep learning model that enables supervised and zero-shot protein function prediction using free-form text inputs, generalizing to unseen functions.

This paper introduces EvoDiff, a diffusion model that generates diverse, high-fidelity proteins in sequence space, overcoming limitations of structure-based models.