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Updated: Jun 13, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
PhenoFam-gene set enrichment analysis through protein structural information.
Maciej Paszkowski-Rogacz1, Mikolaj Slabicki, M Teresa Pisabarro
1Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr, 108, 01307 Dresden, Germany. paszkows@mpi-cbg.de
PhenoFam is a new web tool that combines gene set enrichment analysis (GSEA) with protein structural information to help researchers understand large biological datasets and discover gene functions.
Area of Science:
- Genomics
- Proteomics
- Bioinformatics
Background:
- High-throughput biological studies generate massive datasets requiring advanced analysis tools.
- Gene set enrichment analysis (GSEA) and protein structural investigation are powerful methods for data interpretation.
- A unified tool for combining these approaches in high-throughput data analysis was lacking.
Purpose of the Study:
- To develop a user-friendly, web-based application named PhenoFam.
- To integrate gene set enrichment analysis with protein structural and functional domain information.
- To facilitate the functional annotation of genes from high-throughput data.
Main Methods:
- PhenoFam utilizes Ensembl databases to link user identifiers with InterPro protein domain features.
- It performs GSEA using protein domain families as annotation terms.
- The tool analyzes complete high-throughput study results without pre-filtering.
Main Results:
- PhenoFam successfully identified a novel function of plexins with RasGAP domains from an RNA interference screen.
- Analysis of breast cancer gene expression profiles revealed a connection between PX domain-containing proteins and carcinoma.
- The tool demonstrated its utility in uncovering functional insights from large-scale biological data.
Conclusions:
- PhenoFam offers an accessible web interface for GSEA using high-throughput data and protein structural information.
- The application aids in the functional annotation of genes.
- It addresses the need for integrated tools in analyzing complex biological datasets.
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