Dantong Wang

Nonlinear mixed-effect models and tailored parametrization schemes enables integration of single cell and bulk data

This paper presents a framework for integrating single-cell and bulk data using nonlinear mixed-effect models and tailored parameter estimation, improving parameter identifiability and prediction accuracy.

Multimodal AI Decodes Extreme Environment Functional Dark Matter Beyond Homology

The paper develops ACCESS, a multimodal graph neural network to annotate functional dark matter proteins from extreme environments beyond homology-based methods.

Structural basis of DNA N6-adenine methylation in eukaryotes

This study determines the structural basis of DNA N6-adenine methylation by modeling the AMT1 complex and validating its function through mutagenesis.

SpaGRN: investigating spatially informed regulatory paths for spatially resolved transcriptomics data

SpaGRN predicts spatially informed gene regulatory networks from spatial transcriptomics data, revealing spatiotemporal regulatory patterns in Drosophila development.

Dual modes of DNA N6-methyladenine maintenance by distinct methyltransferase complexes

The paper identifies two distinct methyltransferase complexes that coordinate to maintain DNA N6-methyladenine (6mA) through different mechanisms during replication and transcription.

Cell-to-cell variability in JAK2/STAT5 pathway components and cytoplasmic volumes define survival threshold in erythroid progenitor cells

The paper models single-cell variability in JAK2/STAT5 signaling and cytoplasmic volume to explain how erythroid progenitor cells transition from binary survival/apoptosis decisions to graded population responses upon Epo stimulation.

Dirac mixture distributions for the approximation of mixed effects models

The paper compares methods for approximating mixed effects models, finding that the modified Cramer-von Mises Distance method provides better accuracy than Monte-Carlo and sigma-point methods.