CompaCt
CompaCt performs automated integrative comparative analysis of complexome profiling datasets across multiple species to characterize and compare protein complexes using orthology information.
Key Features:
- Automated Integrative Analysis: Performs fully automated analysis of complexome profiling data derived from separation of intact protein complexes and mass spectrometric analysis of fractions.
- Comparative Approach: Handles datasets from multiple species to identify and compare conserved and taxon-specific components of protein complexes.
- Orthology Leveraging: Utilizes orthologous relationships between proteins across species to enhance comparative identification of conserved elements and taxon-specific features.
Scientific Applications:
- Characterization of Protein Complexes: Integrates multiple complexome profiles to improve characterization of protein complex composition and organization.
- Discovery of Novel Interactors and Complexes: Identifies novel candidate interactors and previously unrecognized protein complexes, including examples such as the emp24 complex, V-ATPase, and mitochondrial ATP synthase.
- Evolutionary Insights: Enables large-scale comparative studies that provide insights into the evolution of metazoan protein complexes, exemplified by analyses in Anopheles stephensi.
Methodology:
Applies integrative and comparative algorithms to complexome profiling datasets and identifies conserved and taxon-specific elements through orthology-based methods.
Topics
Details
- License:
- GPL-3.0
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 10/15/2023
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
Clustering
Inputs
Outputs
Publications
van Strien J, Evers F, Lutikurti M, Berendsen SL, Garanto A, van Gemert G, Cabrera-Orefice A, Rodenburg RJ, Brandt U, Kooij TWA, Huynen MA. Comparative Clustering (CompaCt) of eukaryote complexomes identifies novel interactions and sheds light on protein complex evolution. PLOS Computational Biology. 2023;19(8):e1011090. doi:10.1371/journal.pcbi.1011090. PMID:37549177. PMCID:PMC10434966.
Downloads
- Container filehttps://hub.docker.com/r/joerivanstrien/compact-bio