Fatma-Elzahraa Eid

An AAV capsid reprogrammed to bind human Transferrin Receptor mediates brain-wide gene delivery

The paper develops a modified AAV capsid that targets the human Transferrin Receptor to enhance gene delivery to the CNS, showing improved reporter expression and therapeutic potential for Gaucher disease.

Systematic multi-trait AAV capsid engineering for efficient gene delivery

The paper introduces Fit4Function, a machine learning approach to engineer AAV capsids with multiple traits, achieving high transduction efficiency and cross-species prediction.

Targeting AAV vectors to the CNS via de novo engineered capsid-receptor interactions

This paper identifies AAV capsids that target specific proteins on the blood-brain barrier, enhancing CNS tropism and enabling predictable gene delivery vectors.

Systematic auditing is essential to debiasing machine learning in biology

This paper introduces a systematic auditing framework to identify biases in machine learning applications in biology, showing that biases can hinder model generalizability and lead to poor performance when training data lacks sufficient signal.

A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction

The paper presents a large-scale cancer pharmacogenomic screen with 11,576 experiments on 910 drug combinations across 85 cancer cell lines, enabling crowd-sourced prediction of synergistic drug pairs and biomarkers.