Zexu Li

A comprehensive benchmark for multiple highly efficient base editors with broad targeting scope

The paper benchmarks multiple base editors and develops a model to predict editing efficiency, validating edits for disease-associated variants and identifying cancer-related SNVs.

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer

This study identifies convergent therapeutic targets for chemoresistance in cancer using CRISPR screens across multiple drug conditions and cancer models.

Modeling kidney development, disease, and plasticity with clonal expandable nephron progenitor cells and nephron organoids

This paper develops a synthetic niche to expand nephron progenitor cells, enabling organoid generation and CRISPR screening for kidney development and disease.

Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

The paper develops DeepCas13, a deep learning model to predict CRISPR-Cas13d gRNA on-target activity and off-target viability effects, improving accuracy for RNA editing applications.

Intrinsic RNA targeting constrains the utility of CRISPR-Cas13 systems

The paper evaluates CRISPR-Cas13 systems and finds that they have intrinsic RNA targets in mammalian cells, which can affect lentiviral particle production and limit their utility.

A Chemical-Enhanced System for CRISPR-Based Nucleic Acid Detection

This paper introduces CECRID, a CRISPR-based detection system enhanced with L-proline to improve sensitivity and robustness for nucleic acid detection, particularly for SARS-CoV-2.