Chenling A. Xu

This study combines machine learning and high-throughput screening to design improved nuclease enzymes, finding a more effective variant than standard directed evolution methods.

GENTANGLE is a computational tool for designing overlapping gene pairs in microbial genomes, enabling safer genetic engineering through gene entanglements.

popV improves cell-type annotation by providing uncertainty scores and reducing manual inspection through ensemble voting.

Nearly 500,000 cells from 24 human tissues, many from one donor, characterize over 400 cell types and enable within-donor study of T-cell clones, B-cell mutation rates and splicing.

scvi-tools provides a Python package for probabilistic analysis of single-cell omics data, offering standardized interfaces and extensible tools for various analysis tasks.

This paper introduces scVI and scANVI, deep generative models for integrating single-cell RNA-seq data and annotating cell states, showing improved accuracy and scalability over existing methods.

The paper introduces Cassiopeia, a method for inferring single-cell phylogenies from lineage tracing data, and benchmarks it against traditional methods using a large experimental dataset.

SymSim simulates single cell RNA-Seq data with controlled variability to benchmark clustering and differential expression methods and assess experimental design parameters.