we use Systems Bioinformatics approaches to develop next generation drug discovery tools
IGRENE is a suite of bioinformatics tools designed to integrate Gene Regulatory Networks (GRNs) across multiple biological ontologies using a criteria-driven computational framework. The platform applies a multi-layer systems biology approach to identify drugs, compounds, foods, and molecular regulators that influence the activity of genes of interest through their regulatory network pathways. By combining heterogeneous biological data sources, IGRENE supports the exploration of regulatory mechanisms at different molecular levels and enables the prioritization of candidate drugs and bioactive compounds for experimental validation and therapeutic application. In addition, the framework is designed to support personalized and precision medicine by allowing gene-centric analyses tailored to specific molecular profiles, facilitating the identification of targeted interventions based on individual regulatory network signatures.
we use state of the art approaches for developing
Investigate Drug Influence Networks
Investigate both the activation and suppression networks stemming from a candidate drug to a specific target gene
Projecting Drug Ontologies to GRNs
Project candidate drugs through GRNs to evaluate their potential modulatory effects on a gene of interest
Investigate Gene Influence Networks
Investigate both the activation and suppression networks stemming from a source gene to a specific target gene
we use state of the art approaches for developing
The new upgraded IGRENE platform incorporates the SIGNOR 4.0 and OmniPath data repositories as its primary source for Gene Regulatory Network (GRN) information. Its rich dataset offers mechanistic regulatory information, critical for network-based drug prioritization, enabling precise mapping of the upstream and downstream interactions that influence target gene expression. The platform integrates multiple curated pharmacological and toxicogenomic repositories to support comprehensive drug-gene interaction analysis, as follows: .
(1) The
SIGNOR
database provides experimentally supported causal relationships between drugs, proteins, and signaling pathways.
These curated interactions enable their direct integration into the Gene Regulatory Network (GRN) framework,
supporting mechanistic interpretation of regulatory effects towards improving the accuracy of downstream network-based analyses.
(2) The
OmniPath
database is a comprehensive resource of curated signaling, regulatory, and intercellular communication knowledge,
integrating information from multiple expert-curated databases and literature sources.
These high-confidence causal and directed interactions between proteins, transcription
factors, ligands, receptors, and signaling pathways can be directly incorporated
into the Gene Regulatory Network (GRN) framework.
(3) The
DrugBank
repository serves as a primary resource, providing extensive chemical,
pharmacological, and molecular information, including detailed drug
structures, mechanisms of action, and validated target proteins,
enabling the incorporation of high-confidence drug–target interactions.
(4) The
Drug Gene Budger (DGB)
repository, which aggregates
drug-gene associations derived from the L1000, CREEDS, and CMAP ontologies. Through data-driven modeling approaches, DGB enables the
identification of potential regulatory relationships, offering valuable
insights into drug effects even for compounds with limited direct
experimental evidence.
(5) The
Comparative Toxicogenomics Database (CTD)
resource that captures chemical-gene & compound-gene interactions derived from the scientific literature.
This enables a more comprehensive interpretation of drug and chemical
effects within regulatory networks.
we use Systems Bioinformatics approaches to develop next generation tools
we use parallel processing environments to optimize data handling
We are pleased to introduce the upgraded version of the IGRENE platform, a major extension of our computational framework for gene regulatory network analysis and personalized medicine applications. This new version represents an important step toward the development of a more robust and scalable systems biology framework capable of supporting advanced bioinformatics analyses, translational research, and precision medicine applications.
Minadakis, G., & Spyrou, G. M. (2025). IgRENE: integrating gene regulatory networks and drug ontologies towards selected modification of target gene’s expression. Briefings in Bioinformatics, 26(6), bbaf688.
focusing on new cross collaborations and new research ideas
focusing on new cross collaborations and new research ideas