Data Science Core Facility
The WV-INBRE Data Science Core provides access to cutting-edge AI platforms and computational tools for biomedical research. We specialize in multi-omics analysis, single-cell data translation, and biological network analysis through our partnership with leading computational biology platforms.
Visit Bioinformatics Core WebsiteCore Services
AI Platforms, Knowledge Bases & Tools
G2PDeep Platform
Multi-omics phenotype prediction and marker discovery using deep learning
Key Features
- Deep learning for multi-omics integration
- Automated hyperparameter tuning
- Biomarker discovery and visualization
- Gene Set Enrichment Analysis (GSEA)
crossMP Platform
Cross-modality translation between single-cell RNA-seq and single-cell ATAC-seq data
Key Features
- Deep neural network modeling for modality translation
- Upload one modality, predict the other
- Single-cell multi-omics integration
- Web-based portal with intuitive interface
KBCommons
Knowledge Base Commons for biological data integration, sharing, and community-driven annotation
Key Features
- Integrated biological databases and knowledge graphs
- Data sharing and collaboration tools
- Standardized data formats and ontologies
- Community annotation and curation features
IRNet
Interaction Network analysis tools and databases for regulatory and protein networks
Key Features
- Protein-protein interaction networks
- Gene regulatory networks and pathway analysis
- Network visualization and analysis tools
- Comparative network analysis across species
Core Team
Dr. Jim Denvir, PhD
Core Director
Marshall University
Oversees the Data Science Core operations and strategic direction
Dr. Mohit Verma
Research Assistant Professor
Marshall University
Specializes in AI/ML applications for biomedical research and platform integration
Mohammad Vahed
Research Assistant Professor
Marshall University
Focuses on computational biology, network analysis, and data science training
Funding Support
Supported by the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (NIH)