Yanshuo Chen

CodonTranslator: a conditional codon language model for codon optimization across all domains of life

CodonTranslator is a Transformer-based model for codon optimization across species, achieving better codon usage and stability than existing methods.

LivecellX: Corrective Deep Learning for Object-Oriented Single-Cell Analysis in Live-Cell Imaging

LivecellX corrects segmentation and tracking errors in live-cell imaging using deep learning and provides tools for lineage reconstruction and dynamic analysis.

Inferring Single-Cell RNA Kinetics from Various Biological Priors

This paper introduces scRNAkinetics, a method to estimate RNA kinetics parameters from scRNA-seq data using biological priors, showing accurate inference on simulated datasets and validation with existing studies.

Enhancing Biosecurity with Watermarked Protein Design

This paper introduces a watermarking framework for protein sequences generated by deep learning models to enhance biosecurity while preserving performance and accessibility.

scSniper: Single-cell Deep Neural Network-based Identification of Prominent Biomarkers

scSniper identifies disease biomarkers using a deep neural network, outperforming traditional methods on real-world datasets.

Robust and Accurate Doublet Detection of Single-Cell Sequencing Data via Maximizing Area Under Precision-Recall Curve

This paper introduces RADO, a doublet detection algorithm for single-cell sequencing data that maximizes the area under the precision-recall curve, outperforming existing methods on multiple datasets.

Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis

TAPE deconvolves bulk RNA-seq data into cell-type fractions and gene expression using a deep autoencoder, showing better performance and robustness compared to existing methods.