Murat Can Çobanoğlu

Haisu extends nonlinear dimensionality reduction methods to incorporate hierarchical labels, improving visualization of datasets with parent-child relationships and semi-supervised settings.

TReNCo constructs context-specific transcription factor-gene regulatory networks using TAD boundaries, epigenetic marks, and gene expression data to model cardiac development in mice.

This paper introduces generative Bayesian Dirichlet-multinomial models for cell type annotation in scRNA-seq, showing effective transfer from bulk to single-cell data and meaningful clustering without density assumptions.

EPEE improves TF activity inference by integrating regulatory networks and accounting for shared targets, showing accuracy in immune and cancer contexts.