Genomics at the Nexus of AI, Computer Vision, and Machine Learning
by Shilpa Choudhary, Sandeep Kumar, Swathi Gowroju, Monali Gulhane, R. Sri Lakshmi
1Integrating Genomics and Computer Vision: Unravelling Genetic Patterns and Analyzing Genomic Data
Neha Tanwar1, Sandeep Kumar2*, Garima Singh3 and Monika Bhakta4
1Department of Food Technology, Guru Jambheshwar University of Science and Technology, Hisar, India
2Engineering Cluster, Singapore Institute of Technology (SIT), 10 Dover Drive, Singapore, Singapore
3Department of Law, Bennett University, Greater Noida, India
4Department of Law, Sangam University, Bhilwara, Rajasthan, India
Abstract
In recent years, genomics and computer vision have undergone significant advancements that have profoundly influenced scientific research and healthcare. Genomics, which involves studying an organism’s complete DNA sequence, is crucial in understanding the genetic basis of diseases and designing personalized treatment strategies. Conversely, computer vision, a subfield of artificial intelligence, concentrates on creating algorithms and methodologies for analyzing and interpreting visual data. This chapter offers an overview of the convergence of genomics and computer vision, emphasizing the application of image analysis techniques for genomic data and the detection and analysis of genetic patterns using computer vision methods. The rapid progress in high-throughput sequencing technologies has led to a remarkable increase in the volume of genomic data generated. This abundance of genetic information necessitates efficient and accurate analysis methods, wherein computer vision techniques ...
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