Review Article
Decoding Metabolic Pathway: Leveraging Computational Tools for Insight
Issue:
Volume 13, Issue 1, June 2025
Pages:
1-16
Received:
23 April 2025
Accepted:
7 May 2025
Published:
25 June 2025
DOI:
10.11648/j.cbb.20251301.11
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Abstract: His chapter introduces us to the role of cellular signaling pathways and their significance in understanding the intricate working of an organism’s functioning, life processes and enable us in deepening of our understanding of many diseases. Through time many relevant pathways has been discovered, we are yet to discover more and even identify missing pieces of existing pathways. Use of novel computational tools, that integrates principles from computer science, mathematics, and biology help us to enhance our understanding of signaling pathways. Its significance lies in its ability to predict pathway behavior under different conditions, analyze large signaling networks and model biological processes using tools like BioNetGen, Copasi and Virtual Cell. The biological data is sourced from pathway databases (e.g., KEGG, Reactome, BioGRID). The application of machine learning for pattern recognition and pathway inference and use of AI to predict novel interactions or missing components in pathways aid in decoding signaling networks. Computational tools help us to identify drug targets by modeling pathways. Analysis of pathways further assist in drug discovery and drug re-purposing. Predictive modeling systems gives us new insights into cancer and neuro-degenerative diseases (e.g., Alzheimer's), and autoimmune disorders while engineering novel pathways for biotechnological applications thus enhancing development of synthetic biology.
Abstract: His chapter introduces us to the role of cellular signaling pathways and their significance in understanding the intricate working of an organism’s functioning, life processes and enable us in deepening of our understanding of many diseases. Through time many relevant pathways has been discovered, we are yet to discover more and even identify missi...
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