Bioverse

Bioverse predicts protein function and protein-protein interaction networks and annotates proteomes to enable functional inference and pathway discovery across diverse organisms.

Key Features:

• Functional Annotation: Accepts protein sequences and candidate genomes for functional and structural annotation of individual proteins and complete proteomes.
• Protein Interaction Network Prediction: Uses computational methods that leverage data from other genomes to generate predicted protein-protein interaction networks for novel organisms.
• Network-Based Functional Annotation: Applies a network-based annotation method that operates on both experimentally derived and computationally predicted interaction networks and has been applied to over 50 organisms across all domains of life to annotate previously uncharacterized proteins and assess low-confidence annotations.
• Enhanced Computational Framework: Expands representation of organisms, integrates additional data sources, and implements novel prediction techniques such as network-based annotation.
• Phylogenetic Profiling Integration: Incorporates phylogenetic profiling methods to identify novel pathways in proteomes lacking experimental characterization and to support interaction and function predictions.

Scientific Applications:

• Sequence and Proteome Annotation: Produces functional and structural annotations for individual proteins and whole proteomes from submitted genomes.
• Protein-Protein Interaction Prediction: Generates predicted interaction networks to enable inference of molecular roles and connectivity in organisms without experimental PPI data.
• Functional Inference and Pathway Discovery: Uses network connectivity and phylogenetic profiling to infer protein function and identify novel pathways in uncharacterized proteomes.
• Cross-Species Functional Transfer: Leverages comparative genomic data from multiple genomes to transfer interaction and functional information to novel organisms.

Methodology:

Computational prediction of protein-protein interactions leveraging data from other genomes; network-based annotation applied to both experimental and predicted interaction networks; and incorporation of phylogenetic profiling methods to identify pathways and support function and interaction predictions.