IsoBase

IsoBase identifies functionally related proteins across five major eukaryotic model organisms — Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, and Homo sapiens — by integrating sequence similarity and protein–protein interaction (PPI) networks.

Key Features:

• Multi-species coverage: Contains data for Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, and Homo sapiens.
• Integration of data types: Combines sequence similarity with protein–protein interaction (PPI) network information to improve functional inference.
• IsoRankN algorithm: Employs the IsoRankN algorithm as the core computational method.
• Spectral methods: Uses spectral methods within IsoRankN to integrate sequence and network information.
• Clustering output: Produces clusters of proteins that are functionally related rather than solely sequence-orthologous.
• GO-based validation: Clusters show increased likelihood of shared Gene Ontology (GO) annotations, supporting biological relevance.
• Database scope: Comprises 48,120 proteins organized into 12,693 functionally related clusters.

Scientific Applications:

• Comparative genomics: Identification of conserved, functionally related proteins across model organisms to support cross-species comparisons.
• Functional annotation: Assignment and refinement of protein function based on membership in functionally coherent clusters with shared GO terms.
• Conserved pathway exploration: Investigation of conserved biological pathways and complexes across the five species.
• Orthology detection improvement: Enhanced detection of functionally related proteins beyond traditional sequence-based orthology prediction.

Methodology:

IsoBase applies the IsoRankN algorithm, which leverages spectral methods to integrate sequence similarity and protein–protein interaction (PPI) network information and clusters proteins into functionally related groups.