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Computer-Assisted Analysis of Proteomics and Genomic
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Author(s): Sahil Aggarwal (ABES Engineering College, Ghaziabad, India), Ruchi Jain (ABES Engineering College, Ghaziabad, India), Aayush Agarwal (ABES Engineering College, Ghaziabad, India), Sandeep Saxena (Greater Noida Institute of Technology, Greater Noida, India)and A. K. Haghi (Coimbra University, Portugal)
Copyright: 2025
Pages: 16
Source title:
Computer-Assisted Analysis for Digital Medicinal Imagery
Source Author(s)/Editor(s): Amit Sinha (ABES Engineering College, Ghaziabad, India), Pranshu Saxena (School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India), Sanjay Kumar Singh (University School of Automation and Robotics,Guru Gobind Singh Indraprastha University, East Delhi, India)and Harikesh Singh (JSS Academy of Technical Education, Noida, India)
DOI: 10.4018/979-8-3693-5226-7.ch007
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Abstract
Computer-assisted analysis of proteomics and genomics is a method that uses computational tools and algorithms to analyze and interpret vast amounts of data generated by these investigations. This process aids in identifying patterns, predicting protein functions, understanding gene expression patterns, and identifying potential biomarkers or therapeutic targets. It also allows for the integration of various data sources, such as gene ontologies, pathway databases, and protein-protein interaction networks, providing a comprehensive understanding of cellular functions and diseases. Recent technological advancements have transformed proteomics and genomics, enabling faster and more precise data analysis, which could significantly enhance our understanding of diseases, metabolic processes, and biomolecular interactions. This paper explores how computer-assisted analysis is revolutionizing biological research, reshaping genomics and proteomics, and improving our understanding of diseases and the development of tailored medicines. Combining proteomics and genomes can enhance biomarker identification, expedite drug development, produce personalized treatments, and deepen our understanding of disease causes. The future of biomedical research relies on the successful integration of proteomic and genomic data, necessitating interdisciplinary collaboration and innovation in bioinformatics and analytical techniques.
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