ProteomicsDB

ProteomicsDB aggregates and enables analysis of mass spectrometry (MS/MS)-derived human proteome data to quantify protein abundance, expression patterns, and post-translational modifications across human tissues, cell lines, and body fluids.

Key Features:

• Mass-spectrometry-based human proteome draft: Provides a MS/MS-derived draft of the human proteome capturing protein-abundance differences and cell-type- and time-dependent expression patterns.
• High-performance in-memory database: Uses a high-performance in-memory database architecture to enable real-time analysis of large proteomic datasets.
• Integration across biological samples: Integrates data from human tissues, cell lines, and body fluids into a unified dataset.
• Estimation of protein-coding genome size: Aggregates evidence across samples to support estimation of the size of the protein-coding genome.
• Identification of organ-specific proteins and translated lincRNAs: Identifies organ-specific proteins and a substantial set of translated long intergenic non-coding RNAs (lincRNAs).
• Conserved control of protein abundance: Enables analysis revealing conserved mechanisms controlling protein abundance across tissues.
• Drug-sensitivity and resistance prediction: Integrates drug-sensitivity data to identify proteins that predict resistance or sensitivity to treatments.
• Protein complex composition and stoichiometry analysis: Supports analysis of protein complex composition and stoichiometry.

Scientific Applications:

• Proteomics research: Quantitative analysis of protein abundance, expression dynamics, and post-translational modifications across samples.
• Genomics and systems biology: Integration of proteomic evidence with genomic and systems-level studies to inform biological models.
• Disease mechanism and targeted therapy development: Investigation of disease-related proteomic changes to inform targeted therapy development.
• Personalized medicine and drug response prediction: Identification of proteins predictive of drug sensitivity or resistance to support personalized therapeutic strategies.
• Discovery of organ-specific proteins and translated lincRNAs: Detection of organ-specific proteomes and translated lincRNAs for functional characterization.
• Protein complex and stoichiometry studies: Analysis of complex composition and stoichiometry to understand molecular machinery and interactions.

Methodology:

Analysis of mass spectrometry (MS/MS) data using a high-performance in-memory database to enable real-time integration of datasets from human tissues, cell lines, and body fluids.