ImmCellFie

ImmCellFie infers metabolic functions and quantifies cellular metabolic activity from transcriptomic or proteomic datasets to interpret omics-derived metabolic phenotypes.

Key Features:

• Omics data integration: Integrates and interprets transcriptomic and proteomic datasets, including data from public databases, to relate molecular measurements to metabolic function.
• Metabolic function inference: Infers metabolic functions from complex biological datasets to characterize cellular metabolism.
• Advanced algorithmic approach: Employs an algorithm that integrates complex biological mechanisms and extends beyond conventional statistical enrichment methods.
• Quantitative activity assessment: Quantifies cell metabolic activity rather than relying solely on enrichment statistics.
• Visualization capabilities: Provides visualization options to support interpretation of inferred metabolic functions.

Scientific Applications:

• Biotechnology research: Applied to analyze cellular metabolic functions in biotechnology contexts using omics data.
• Biomedical research: Used to study metabolic states in normal physiological processes and pathological conditions from transcriptomic or proteomic datasets.
• Mechanistic investigations: Supports investigations aimed at elucidating underlying metabolic mechanisms from omics measurements.

Methodology:

Analyses are configured using transcriptomic or proteomic datasets (including public databases) and processed by an algorithm that infers metabolic functions by integrating complex biological information beyond traditional statistical enrichment methods, as described in Richelle et al. (2021).