SYSTEMS BIOLOGY FRAMEWORK FOR UNDERSTANDING CELLULAR RESPONSE NETWORKS

Abstract

Cellular response networks are the systems that regulate the biology of perception, processing, and adaptation of biology to internal and external factors through the interaction of genes, proteins and signaling pathways. Although molecular biology has made major progress, the available knowledge is at present disjointed as a result of the compartmentalized study of each of the omics layers, and it is impossible to reach the complexity of cellular behavior. This work fills this gap by suggesting an integrative systems biology paradigm to holistically model and analyze cellular response networks. The framework proposed utilizes the multi-omics integration of data and uses genomics, transcriptomics and proteomics to build a coherent explanation of cell events. Skilled computational methods, such as network modeling, graph-based analysis, machine learning methods, etc., are utilized to recognize important regulatory interactions and dynamic pathway behaviors. The framework allows understanding of cellular responses on a systems-level when heterogeneous biological measurements are integrated, and their interrelationships are modeled. The use of such framework enables the identification of key regulatory pathways, interaction networks and molecular signatures that regulate cellular adaptation and dysfunction. Additionally, it offers a predictive platform to model the effects that cells will make when perturbed, e.g. disease development or therapeutic intervention. In general, this systems biology paradigm provides a scalable and powerful methodology to decode the complex cellular response mechanisms, and it has far-reaching implications on disease biology, biomarker discovery, and precision medicine.