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Functionathon: a manual data mining workflow to generate functional hypotheses for uncharacterized human proteins and
Paula Duek1,2, Camille Mary2, Monique Zahn-Zabal1
1CALIPHO group, SIB Swiss Institute of Bioinformatics.
Summary
Researchers developed a workflow to predict functions for uncharacterized human proteins. This method, applied in an undergraduate course, proposed functions for seven proteins in areas like cilia, lipid, and RNA metabolism.
Area of Science:
- Proteomics
- Bioinformatics
- Genomics
Background:
- Approximately 10% of human proteins lack functional annotation in current knowledge bases.
- Understanding protein function is crucial for biological and medical research.
- The Human Proteome Organization (HUPO) initiated a project to address these annotation gaps.
Purpose of the Study:
- To develop and apply a workflow for generating functional hypotheses for uncharacterized human proteins.
- To train undergraduate students in using bioinformatics tools for functional annotation.
- To contribute to the HUPO Human Proteome Project's goals.
Main Methods:
- A workflow integrating predicted and experimental data was developed.
- Data sources included protein properties, interactions, expression, localization, conservation, and phenotypic data.
- The workflow was applied to seven uncharacterized human proteins (C6orf118, C7orf25, CXorf58, RSRP1, SMLR1, TMEM53, TMEM232) during a Functionathon course.
Main Results:
- Functional hypotheses were generated for the seven studied proteins.
- C6orf118, CXorf58, and TMEM232 were linked to cilia-related functions.
- TMEM53 and SMLR1 were proposed to be involved in lipid metabolism.
- C7orf25 and RSRP1 were suggested to play roles in RNA metabolism and gene expression.
Conclusions:
- The developed workflow effectively generates testable hypotheses for uncharacterized proteins.
- The Functionathon course successfully trained students in bioinformatics and data interpretation.
- The findings contribute valuable functional insights for the HUPO Human Proteome Project.
