All ETDs from UAB

Advisory Committee Chair

Shahid Mukhtar

Advisory Committee Members

Mohammad Athar

Anupam Agrawal

John Hartman

Elizabeth Worthy

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) College of Arts and Sciences


The accelerated growth in sequencing technology assisted us to explore the bio-logical systems comprehensively through a top-down approach rather than the conven-tional bottom-up approach. The top-down approach is a part of systems biology that gen-erates 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 (biomole-cules) 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 integra-tion and analysis of qualitative and quantitative associations. These associations maintain the global circuitry of diverse biological processes and signaling pathways induced dur-ing 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 po-tentially influence the condition-specific biological pathway during stress. Therefore, de- iv coding 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 dis-eases. 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.



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