Chieh Hubert Lin

This paper introduces LinTIMaT, a method that integrates CRISPR-Cas9 mutation and transcriptomic data to reconstruct lineage trees with improved accuracy and coherence.

The paper maps cell fate trajectories of human PSC-derived distal lung progenitors using scRNA-seq and identifies developmental plasticity regulated by Wnt signaling.

The paper introduces a continuous state HMM method for modeling time series scRNA-Seq data, showing improved accuracy in inferring branching topology and cell path assignments.

The paper develops a method to detect cell type-specific mutations from scRNA-Seq data and integrates them with expression data to improve lineage reconstruction.

The paper develops a neural network method to improve single-cell RNA-Seq analysis by better grouping cells and inferring cell types from expression profiles.