Systems Bio
Gene Networks
Genes do not operate in isolation; they are in constant interaction and communication with one another. Profiling these interactions uncovers potential targetable pathways that may not be revealed through simple statistical analyses. Gene networks provide a comprehensive view of gene interactions, aiding in the identification of new targets or the validation of existing ones. We build and analyze these gene networks using next-generation sequencing data from genomics and epigenomics.
Gene Co-expression Networks
Gene co-expression networks identify genes that act in concert and are likely to be functionally related. By employing correlation-based approaches, as well as other advanced methods, we construct these co-expression networks to capture the dynamic relationships between genes. The resulting network offers a comprehensive view of genes whose activities are closely correlated, providing insights into their roles in disease mechanisms and response to therapeutic interventions. This approach enables the identification of potential biomarkers and novel therapeutic targets by revealing gene clusters that share common regulatory patterns.
Gene Regulatory Networks
Gene regulatory networks (GRNs) are similar to gene co-expression networks, but with an important distinction. Instead of merely reflecting gene correlations, GRNs provide a regulatory perspective by incorporating directionality information. This reveals which genes are controlling the activity of other genes, offering deeper insights into the regulatory relationships that govern cellular functions and disease processes.
Transcriptional Regulatory Networks
Transcriptional regulatory networks (TRNs) specifically focus on transcriptional control, a crucial aspect of gene regulation. These networks highlight the role of transcription factors (TFs) in orchestrating gene expression. By mapping the interactions between TFs and their target genes, TRNs enable the identification of key transcriptional regulators that drive or inhibit processes such as cell differentiation. Understanding these networks is essential for uncovering the molecular mechanisms underlying development, disease, and therapeutic responses.
