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Updated: May 7, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis
Published on: July 12, 2022
SUS-BAR: a database of pig proteins with statistically validated structural and functional annotation
Damiano Piovesan1, Giuseppe Profiti, Pier Luigi Martelli
1Bologna Biocomputing Group, University of Bologna, via S. Giacomo 9/2, I-40126, Bologna, Italy, Department of Biological, Geological and Environmental Sciences (BIGEA), University of Bologna, via Selmi 3, I-40126, Bologna, Italy, Department of Computer Science and Engineering, University of Bologna, Mura A. Zamboni 7, I-40126, Bologna, Italy, Health Science and Technologies-ICIR, University of Bologna, Via Tolara di Sopra 41/E, I-40064, Ozzano dell'Emilia, Italy and Department of Agro-Food Science and Technology (DISTAL), University of Bologna, Viale Fanin 46, I-40127, Bologna, Italy.
The SUS-BAR database offers statistically validated functional and structural annotations for over 16,000 pig protein sequences, improving understanding of pig biology and disease. This resource enhances pig proteome research by providing reliable gene and protein information.
Area of Science:
- Bioinformatics
- Proteomics
- Comparative Genomics
Background:
- The pig proteome is crucial for understanding human diseases, but currently lacks comprehensive annotation.
- Existing pig protein annotation relies heavily on automated sequence alignment, leading to inaccuracies.
- A significant portion (approximately 80%) of the pig proteome remains poorly annotated, hindering biological research.
Purpose of the Study:
- To introduce SUS-BAR, a novel database providing statistically validated functional and structural annotations for pig protein sequences.
- To improve the understanding of pig genes and proteins in biological processes and disease.
- To offer a searchable resource for pig proteome data with enhanced annotation quality.
Main Methods:
- Developed SUS-BAR database integrating data primarily from UniProt Knowledgebase, containing 26,206 pig protein sequences.
- Implemented a cluster-centric annotation procedure for statistically validating functional and structural information.
- Associated each sequence with validated Gene Ontologies (GOs), Pfam domains, and Hidden Markov Models for 3D structure where applicable.
Main Results:
- SUS-BAR provides statistically validated annotations for 16,675 pig protein sequences.
- The database demonstrates enrichment in Gene Ontology (GO) and Pfam annotations compared to existing UniProt Knowledgebase annotations.
- Enables retrieval of pig protein annotation based on GO terms or structural characteristics.
Conclusions:
- SUS-BAR significantly enhances the annotation quality of the pig proteome.
- The database serves as a valuable resource for researchers studying pig biology, genetics, and disease.
- Facilitates detailed analysis of pig protein function, structure, and involvement in biological pathways.
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