NetMap is presented, a pipeline that jointly infers cell-level GRNs and clusters cells based on shared regulatory programs, combining state-of-the-art single-cell autoencoders and explainable artificial intelligence methods that outperforms existing methods on synthetic data with a known ground-truth GRN and is able to...
A. Hartebrodt, Mhaned Oubounyt, G. D. de Almeida et al.· bioRxiv· 0 citations
Protein-protein interactions (PPIs) have been detected and reported in the millions, but while they are used in many different contexts for better understanding cellular processes in health and disease, the knowledge of the human PPI network is far from complete, containing many false positive measurements and being hi...
Joel Ås, K. Pelz, J. Bernett et al.· bioRxiv· 1 citation
SignifiKANTE employs gene clustering based on the 1-Wasserstein distance to create a small, constant number of background distributions which enables the simultaneous computation of approximate empirical P-values for multiple target genes, which reduces runtime by orders of magnitudes.
F. Woller, Paul Martini, Souptik Sen et al.· bioRxiv· 1 citation
A benchmarking study on multiple GNNs on a Protein-Protein Interaction (PPI) network for Kidney Renal Clear Cell Carcinoma and Breast cancer subtype prediction, performing an in-depth investigation of architectures, incorporating skip connections and various data modalities.
Julia Schirmacher, M. C. Maurer, J. M. Metsch et al.· bioRxiv· 0 citations
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