The Integrative Systeomics Framework to Prioritize Genes and/or Pathways in Skin Inflammation

Abstract

The accelerated growth in sequencing technology assisted us to explore the biological systems comprehensively through a top-down approach rather than the conventional bottom-up approach. The top-down approach is a part of systems biology that generates massive data that has driven this course of investigation to decipher the system-wide genetic perturbations. To reduce the complexity of humongous datasets, the graph (network)-based techniques facilitate the easy handling, analysis, and interpretation of biological associations. Networks are the graphical representation of nodes (biomolecules) and edges (associations/interactions). The most common biological networks are correlation-based gene co-expression network (GCN), gene regulatory network (GRN), and protein-protein interaction (PPI) network. The addition of several multidimensional datasets and networks has presented an enormous challenge through efficacious integration and analysis of qualitative and quantitative associations. These associations maintain the global circuitry of diverse biological processes and signaling pathways induced during any stress. Exploration of structural and functional properties of these networks holds high potential to reveal a wide range of information on the specific regulator, proteins, and interactions within signaling cascades. The structural properties define the network robustness, resilience, and identify the significant components in the network. It is known that few nodes (proteins/genes) structurally positioned themselves in a way that, can potentially influence the condition-specific biological pathway during stress. Therefore, decoding the network structural architecture and exploiting these topological properties are crucial to revealing the novel components in a multifaceted system, which may lead to the identification of key players in biological processes. In this work, I explored network-centric approaches in different biological conditions including basal cellular hemostasis, viral infection, chemical-induced skin inflammation, and eight immune-system skin diseases. Finally, I have designed and optimized a flexible framework through an integrative systeomics approach to prioritize the most vulnerable genes/proteins that have a high probability to alter signaling pathways during skin inflammation.