An Automated Web Server to Construct Biomolecular Networks for Translational Cancer Systems Biology
A robust cancer model starts with acquiring nodes from diverse, high-value sources. We integrate Genomic Data Commons (GDC) datasets, frequently mutated nodes, cancer signature genes, and therapeutic targets to ensure biological relevance and translational potential. By aggregating data from these authoritative sources, we build a comprehensive, data-driven foundation for precision oncology.
We enhance node relevance by leveraging Enrichr, MSigDB, and curated pathway databases to analyze molecular functions, cellular components, and biological processes. This enrichment refines our network, uncovering key interactions and pathways essential for understanding cancer biology and therapeutic targeting.
We integrate the enriched node set into a comprehensive interactome using in-built databases such as INDRA, TRRUST, SIGNOR, and Omnipath. These resources provide activation and inhibition relationships, enabling the construction of a biologically informed network that maps key molecular interactions, regulatory mechanisms, and signaling pathways essential for cancer research.
Using RNA sequencing data and interactome maps, we annotate network nodes to construct optimal Boolean network models. These models enable simulation and analysis, supporting downstream applications in cancer research and therapeutic discovery.
Scientific Reports - Nature
Frontiers in Oncology - Special Issue on "Combinatorial Approaches for Cancer Treatment"
Frontiers in Oncology - Special Issue on "Combinatorial Approaches for Cancer Treatment"
bioRxiv - the preprint server for Biology
Our talented and passionate team members who make everything possible.
A walkthrough of breast cancer network construction.
A walkthrough of the prostate cancer network construction.
Network construction in AutoNetCan and visualization in Cytoscape.
Network construction in AutoNetCan with visualization and analysis in TISON.
Network visualization in Cosmograph.
Biomedical Informatics and Engineering Research Laboratory (BIRL), Department of Life Sciences, School of Science and Engineering, Lahore University of Management Sciences (LUMS), Lahore, Pakistan
Fill out the form below and we'll get back to you as soon as possible.