MStoCIRC

MStoCIRC predicts proteome-wide translatable circular RNAs (circRNAs) by analyzing raw tandem mass spectrometry data and integrating translational evidence such as internal ribosome entry sites (IRES).

Key Features:

• Proteome-wide prediction: Performs proteome-wide prediction of translatable circRNAs.
• Tandem mass spectrometry analysis: Analyzes raw tandem mass spectrometry data for peptide evidence supporting circRNA translation.
• Integration of translational evidence: Incorporates internal ribosome entry sites (IRES) as additional evidence for translation potential.
• Implementation and modularity: Implemented in Python3 as a main program with several independent function modules.
• Cross-species identification: Has identified hundreds of candidate translatable circRNAs in humans and Arabidopsis thaliana.

Scientific Applications:

• Discovery of translatable circRNAs: Enables proteome-wide discovery of circRNAs with peptide-level evidence from mass spectrometry.
• Assessment of translation potential: Combines peptide evidence and IRES annotation to assess the translation potential of circRNAs.
• Comparative organismal analysis: Supports identification and comparison of candidate translatable circRNAs in humans and Arabidopsis thaliana.

Methodology:

Analyzes raw tandem mass spectrometry data and integrates internal ribosome entry site (IRES) evidence; implemented in Python3 with a main program and independent function modules.