Genomics at the Nexus of AI, Computer Vision, and Machine Learning explores the in-depth process of how AI and machine learning algorithms extract genomic data. The main goal is to help readers understand the dynamic intersection between genomics and cutting-edge technologies. This book aims to provide a roadmap for navigating genomics with developments in artificial intelligence to open up new research ideas to detect and analyze genetic patterns using computer vision methods.
This book encompasses a wide range of topics, starting with an introduction to genomics data and its unique characteristics. Each chapter unfolds a unique facet, delving into the collaborative potential and challenges that arise from advanced technologies. It explores image analysis techniques specifically tailored for genomic data. With this resourceful data, research enables the detection and analysis of genetic patterns using computer vision methods. Furthermore, the dedicated research from contributors offers insights and knowledge to genomic research that seeks to explore the mysteries of life through the lens of interdisciplinary collaboration.
Shilpa Choudhary, Ph.D., is a postdoctorate at the Singapore Institute of Technology, Singapore. Her research interests include medical image processing, IoT, machine learning, and deep learning. She has authored more than 50 research papers in various national and international journals. She has been awarded nine patents and was awarded the ‘Gold Medal’ in 2012 during her M.Tech. studies.
Sandeep Kumar, Ph.D., is a professor in the Department of Computer Science and Engineering, K L Deemed to be University, Vijayawada, Andhra Pradesh, India. He has been granted six patents and has successfully filed another ten. He has published more than 100 research papers in various national and international journals and proceedings at reputed national and international conferences.
G. Swathi, Ph.D., is an associate professor and deputy head of the Data Science Department, Sretas Institute of Engineering and Technology, Hyderabad, Telangana, India. Her research area is molecular image processing and machine learning. She has published more than 30 research papers in the fields of image processing and machine learning. She has been a reviewer for many reputed SCI and Scopus journals.
Monali Gulhane, Ph.D., is an assistant professor at the Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, India. Her research specializations include machine learning, deep learning, and artificial intelligence. She is a speaker for data visualization in the industry of data analytics tools. She received the 'Young Researcher Award' in 2022 for persistent work in the area of research.
R. Sri Lakshmi, Ph.D., is a postdoctorate at the Singapore Institute of Technology, Singapore. Her research focuses on artificial intelligence, machine learning, and deep learning. She is proficient in subjects such as machine learning, artificial intelligence, computer design, etc. She has been actively involved in various academic and administrative responsibilities and supervised numerous real-time projects. Most of her research has been published in renowned journals, patents, and chapter books.
