SYSBIOMAP
AI-Powered Disease Map Construction and Validation
AI-Powered
Systems Biology
Platform
Accelerating disease mechanism discovery through systems biology, signaling networks, and computational therapeutic discovery.
✓ Literature Mining & Knowledge Extraction
✓ Disease Map Validation & Annotation
✓ CellDesigner-Compatible Workflows
What SYSBIOMAP Does
SYSBIOMAP combines artificial intelligence, systems biology, literature mining, and expert curation to accelerate disease map construction, validation, and therapeutic target discovery.
AI Modeling
Build predictive biological models using machine learning and network analysis
Systems Biology
Analyze signaling pathways, molecular interactions and disease mechanisms
Therapeutic Discovery
Identify novel targets and accelerate computational therapeutic discovery of drugs
Who Benefits from SYSBIOMAP?
Academic Researchers
✓ Literature mining
✓ Disease maps
✓ Pathway analysis
✓ Hypothesis generation
Disease Map Consortia
✓ Large-scale curation
✓ Annotation workflows
✓ Validation support
✓ CellDesigner maps
Pharma & Biotech
✓ Target discovery
✓ Mechanism discovery
✓ Translational biology
✓ Drug discovery
SYSBIOMAP Methodology
SYSBIOMAP integrates artificial intelligence, systems biology, literature mining, and expert validation to accelerate disease map construction and therapeutic target discovery.
SYSBIOMAP Validation Framework
Why SYSBIOMAP?
SYSBIOMAP combines artificial intelligence and expert biological curation to accelerate disease map construction. The platform assists researchers through literature mining, interaction extraction, evidence tracking, annotation support, and validation while maintaining scientific accuracy through expert review.
Current Validation Studies
✓ SARS-CoV ORF3a Disease Map Validation✓ Colorectal Cancer (CRC) Disease Map Validation✓ AI-Assisted Literature Mining and Interaction Extraction✓ MIRIAM Annotation and Network Standardization✓ CellDesigner-Compatible Disease Map Construction
Coming Soon
• Automated Disease Map Validation• AI-Assisted Interaction Discovery• Evidence-Based Network Reconstruction• Disease Map Quality Assessment• Interactive Systems Biology Knowledge Base
Research & Publications
Preprint | bioRxiv | 2025
Integrative Network Modeling of Colorectal Cancer Reveals Diagnostic Signatures and Therapeutic Targets
This study presents an integrative colorectal cancer molecular interaction map, logic-based modeling framework, disease signature prediction, therapeutic target identification, and validation using patient datasets and machine learning.
Publication | Nature Molecular Systems Biology | 2021
COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms
The COVID-19 Disease Map is a collaborative systems biology resource that integrates virus–host interactions, signaling pathways, and molecular mechanisms associated with SARS-CoV-2 infection. The platform supports computational modeling, pathway analysis, and therapeutic target discovery through a curated knowledge repository.
About the Founder
Muhammad Naveez is a systems biology researcher focused on disease pathway modeling, network biology, and AI-assisted biological knowledge discovery. His research includes colorectal cancer network modeling and contributions to the COVID-19 Disease Map initiative. Through SYSBIOMAP, he aims to accelerate disease mechanism discovery and therapeutic target identification using AI and systems biology.