Dietmar Zehn

NetMap jointly infers cell-level gene regulatory networks and clusters cells based on shared regulatory programs, outperforming existing methods on synthetic data and reliably detecting regulons on real data.

This paper introduces SwitchTFI, a method to identify transcription factors driving cell differentiation using single-cell RNA sequencing data, and shows it outperforms existing methods in functional coherence.

PySCNet is a tool for reconstructing and analyzing gene regulatory networks from single-cell RNA-seq data, offering methods for gene co-expression module detection and gene importance evaluation.

The paper introduces Scellnetor, a tool to identify systems biology patterns in pseudo-temporal trajectories from scRNA-seq data, applied to hematopoiesis and CD8 T-cell development.