XDeathDB

XDeathDB integrates and visualizes molecular interaction networks of twelve cell death modes to elucidate signaling crosstalk and identify potential druggable targets and hallmark genes in cancer and COVID-19.

Key Features:

• Comprehensive Data Integration: Aggregates literature-derived datasets and public databases iRefIndex, STRING, BioGRID, Reactom, Pathway's Commons, DisGeNET, DrugBank, and the Therapeutic Target Database (TTD) covering gene-disease associations, gene–cell death pathway associations, and pathway–cell death mode associations.
• Cell death modes coverage: Represents interactions among 12 cell death modes: apoptosis, autosis, efferocytosis, ferroptosis, immunogenic cell death, intrinsic apoptosis, lysosomal cell death, mitotic cell death, mitochondrial permeability transition, necroptosis, parthanatos, and pyroptosis across 1461 cancer types and COVID-19.
• Multilayer Spectral Graph Clustering: Applies multilayer spectral graph clustering with convex layer aggregation to identify crosstalk functions and highlight potential druggable targets and hallmark genes.
• Network visualization: Visualizes interdependent molecular interaction networks to enable focused examination of specified relationships within cell death networks.

Scientific Applications:

• Deciphering Signaling Networks: Maps intricate signaling networks involved in physiological and pathological cell death to support mechanistic studies.
• Facilitating Drug Discovery: Identifies potential druggable targets and hallmark genes within cell death crosstalk networks to support systems-oriented drug discovery in cancer and COVID-19.

Methodology:

Employs multilayer spectral graph clustering with convex layer aggregation to analyze interdependent molecular interaction networks and identify crosstalk functions and hallmark genes.