Shengdi Li

RankMap improves cell type annotation in spatial and single-cell transcriptomics by using rank-based representations and multinomial regression, achieving competitive accuracy and faster runtime.

The paper introduces RiboGRAM, a model that learns non-coding RNA sequence grammar for structural and regulatory inference across multiple organisms.

The paper introduces scPRIME-seq, a multimodal single-cell platform, and finds pre-neoplastic epigenetic changes drive tumor progression in prostate cancer.

CODIAC profiles spatial protein localization and abundance changes using image-enabled sorting and machine learning, detecting perturbation effects on the spatial proteome.

The paper introduces UbSeRP to map co-translational ubiquitination across the translatome, revealing RQC substrates, biophysical features predicting RQC, and aging-related changes in CTU.

The paper improves CRISPR-Cas12a-assisted gene tagging in mammalian cells by enhancing HDR efficiency and reducing off-target integrations through modified cassettes and repair pathway modulation.

The paper develops MAGESTIC 3.0, a CRISPR-based system for genome-wide variant installation in yeast, revealing missense variants and multiple causal variants in quantitative trait loci across environmental conditions.

This study uses base editors and AAVMYO to correct Rbm20 mutations in cardiomyocytes, improving splicing and cardiac function in mouse models of dilated cardiomyopathy.

The paper describes a fast, low-cost method for preparing whole-genome sequencing libraries from yeast cells, enabling high-throughput analysis of genetic edits and polymorphisms.