Genomics at the Nexus of AI, Computer Vision, and Machine Learning

20Genomics and Machine Learning: ML Approaches, Future Directions and Challenges in Genomics

Sunita Gupta^1*, Neha Janu², Meenakshi Nawal³ and Anjali Goswami⁴

¹Department of Information Technology, Swami Keshvanand Institute of Technology Management and Gramothan, Jaipur, India

²Department of Computer Science and Engineering, Manipal University Jaipur, Rajasthan, Jaipur, India

³Department of CSE, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, India

⁴Department of Basic Sciences, College of Science & Theoretical Studies, Saudi Electronic University, Riyadh Female Campus, Riyadh, Saudi Arabia

Abstract

The chapter of the book “Genomics and Machine Learning: ML Approaches, Future Directions and Challenges in Genomics” delves into the burgeoning intersection of genomics and machine learning (ML). With the advent of high-throughput sequencing technologies, genomics has witnessed a data explosion, necessitating advanced computational techniques to unlock its full potential. This chapter presents an overview of the introduction to genomics, genomics data and its unique characteristics, and the significance of genomics data in artificial intelligence (AI) and ML. It also presents an overview of ML approaches applied in genomics research and their applications, highlighting their contributions to genomic data analysis, gene expression prediction and disease classification. Moreover, it explores the exciting potential of ML in personalized medicine, offering ...