Data files

Primers_TiMet_AnnaFlis2013 (from BioDare)

RNA LD to Both LL and DD (from BioDare)

List of samples used in the assay (extracted from original BioDare metadata and converted to csv)

Original BioDare metadata, converted to json format

Readme file

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Cell-type-specific marker genes were identified from the KPMP-derived transcriptomic dataset. For each cell type, a protein-protein interaction network was generated using STRING interactions among the identified genes. Network topology was analyzed using NetworkX, and multiple centrality metrics were computed to characterize gene importance and identify potential hub genes within each cellular context.

Biochemical Reaction Networks Biochemical Reaction Networks transform static protein-protein interactions (PPI) network into dynamic, mechanistic models by decomposing each interaction into underlying molecular events like phosphorylation and complex formation. Using SPADAN toolbox (DOI:10.1093/bioinformatics/btad079), we expands PPI network into biochemical reactions network.

Ordinary Differential Equation Model Equations Kinetic descriptions of biochemical reactions related to each renal cell ...