Quantitation of Molecular Pathway Activation Using RNA Sequencing Data.

Area of Science:

• Molecular Biology
• Systems Biology
• Bioinformatics

Background:

• Intracellular molecular pathways (IMPs) orchestrate cellular functions and are critical for understanding biological processes.
• Thousands of IMPs have been identified, necessitating robust methods for their analysis.
• Understanding IMP activation is key to differentiating biological objects at a molecular level.

Purpose of the Study:

• To introduce the Oncobox system for accurate, quantitative scoring of thousands of intracellular molecular pathways.
• To demonstrate the system's applicability across diverse high-throughput molecular data types.
• To provide a versatile tool for analyzing various biological pathways.

Main Methods:

• Development of the Oncobox system for quantitative scoring of molecular pathway activities.
• Integration of modules for gene expression data harmonization, aggregation, and comparison.
• Implementation of a recursive algorithm for automatic annotation of molecular pathways.
• Adaptability for gene expression (RNA sequencing), quantitative proteomics, microRNA, and transcription factor binding site data.

Main Results:

• Oncobox enables accurate quantitative scoring of up to several thousand molecular pathways.
• The system is applicable to multiple high-throughput data types beyond initial RNA sequencing focus.
• Oncobox facilitates the scoring of diverse pathways including signaling, metabolic, and immune pathways.

Conclusions:

• The Oncobox system offers a universal approach for scoring molecular pathways across various biological objects.
• It is a valuable tool for researchers in genetics, biochemistry, interactomics, and big data analytics.
• Oncobox enhances the understanding of cellular functions and molecular variations through pathway analysis.