transite

transite systematically infers RNA-binding proteins influencing gene expression through changes in RNA stability and degradation by leveraging preexisting gene expression data and current knowledge of binding preferences of RNA-binding proteins.

Key Features:

• Motif-based analysis: Identifies RNA-binding proteins modulating changes in gene expression through computational motif-based analysis.
• Gene expression data integration: Leverages preexisting gene expression data for comprehensive analysis of RNA-binding protein regulatory roles.
• Binding preference knowledge utilization: Incorporates current knowledge of binding preferences of RNA-binding proteins.
• RBP inference: Systematically infers RNA-binding proteins responsible for observed changes in RNA stability and degradation.

Scientific Applications:

• Cancer research: Identifies RNA-binding protein regulators of the DNA damage response and modulators of chemotherapeutic resistance in non-small-cell lung cancer.
• Cell-state transition analysis: Serves as a framework for identification of RNA-binding proteins that drive cell-state transitions.
• Public data reanalysis: Adds value to publicly available gene expression datasets by identifying RNA-binding proteins underlying observed expression changes.

Methodology:

Computational motif-based analysis approach that systematically infers RNA-binding proteins influencing gene expression through changes in RNA stability and degradation.