SC2MeNetDrug

SC2MeNetDrug identifies intercellular signaling networks and predicts candidate therapeutic drugs from single-cell RNA sequencing (scRNA-seq) data to characterize cell-cell communications in disease microenvironments, including tumor microenvironments and neuronal environments such as in Alzheimer’s Disease.

Key Features:

• Identification of Cell Types: Performs cell type identification and characterizes cellular heterogeneity and sub-populations from scRNA-seq data.
• Uncovering Dysfunctional Signaling Pathways: Detects dysfunctional signaling pathways within individual cell types and infers intercellular interactions that may contribute to disease progression or therapeutic resistance.
• Prediction of Effective Drugs: Predicts drugs that can potentially disrupt identified cell-cell signaling communications to propose candidate therapeutic regimens.
• Integration of External Data Resources: Integrates scRNA-seq analysis with external supportive data resources to map complex signaling networks.

Scientific Applications:

• Disease Progression Analysis: Analyzes cell-cell communication within microenvironments (MEs) to identify interactions influencing disease progression and potential intervention targets.
• Immunotherapy Response: Identifies critical signaling pathways and drug candidates that may modulate immune cell communications relevant to immunotherapy outcomes.

Methodology:

Integrates scRNA-seq data analysis with external supportive data resources to map complex signaling networks.