Daniel Marbach

Comparison of Fixed Single Cell RNA-seq Methods to Enable Transcriptome Profiling of Neutrophils in Clinical Samples

This study compares single-cell RNA-seq methods for neutrophil transcriptome profiling in clinical samples, finding all methods produce high-quality data with 10X FLEX showing strong concordance with flow cytometry.

Contextual AI models for single-cell protein biology

This paper introduces a geometric deep learning model for context-aware protein representations, improving therapeutic target nomination in immune-related diseases.

MONET: a toolbox integrating top-performing methods for network modularisation

MONET provides a unified toolbox for disease module identification in molecular networks using top-performing methods from the DMI DREAM Challenge.

Assessment of network module identification across complex diseases

The paper evaluates module identification methods across disease-relevant networks using GWAS data to identify top-performing algorithms and disease-associated modules.

Gene-set enrichment with regularized regression

This paper introduces a regression-based approach for gene-set enrichment analysis that identifies sparse, interpretable gene-sets for genes of interest.

Intra- and inter-chromosomal chromatin interactions mediate genetic effects on regulatory networks

The paper combines regulatory element activity, gene expression, and genetic variation data across cell types to show how chromatin structure influences regulatory networks and genetic effects.

Predicting trait regulators by identifying co-localization of DNA binding and GWAS variants in regulatory regions

CONVERGE identifies co-localization of GWAS variants with transcription factor binding sites in regulatory regions to find novel trait regulators, outperforming existing methods in validating type 2 diabetes regulators.

Genome-wide association between transcription factor expression and chromatin accessibility reveals chromatin state regulators

The paper identifies transcription factors associated with chromatin accessibility using a linear mixed model applied to ENCODE data, confirming known and suggesting novel regulators.