Gesine Reinert

This study uses fMRI data to analyze brain state dynamics during deep anaesthesia, finding that anaesthesia is dominated by low-complexity attractor states that differ from wakefulness.

The paper introduces a method to construct weighted gene coexpression networks using signed distance correlation, showing improved stability and biological information capture compared to Pearson correlation and unweighted networks.

The paper introduces signed distance correlation to build gene coexpression networks from gene expression data, showing improved stability and biological relevance compared to Pearson or Spearman correlations.

This paper introduces a method to detect functional modules in single-cell RNA sequencing data by integrating with protein-protein interaction networks, revealing biology beyond differential expression analysis.

COGENT evaluates gene co-expression network consistency across different construction methods without external validation data.

This paper shows that hypergraphs better capture multiprotein complex data properties than pairwise graphs, leading to more accurate gene-essentiality predictions.

The paper evaluates the robustness of node metrics in protein interaction networks across different confidence score thresholds and identifies four robust metrics.