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

14Optimum Detection of Human Genome Related to Cancer Cells Using Signal Processing

Manoranjan Dash¹ and Ritesh Raj^2*

¹Artificial Intelligence Department, Anurag University, Hyderabad, India

²Amrita School of Artificial Intelligence, Bengaluru, Amrita Vishwa Vidyapeetham, India

Abstract

Advanced signal-handling techniques are becoming progressively significant in gene identification, biological diagnosis of diseases and sequencing analysis. The twenty amino acids included in DNA are the fundamental building blocks of protein. Clinical analysts say a few amino acids are exceptionally connected with malignant growth infections. In the current chapter, the authors have shown a relatively otherworldly examination of amino corrosive chains for different diseases and non-malignant growth cells utilizing digital signal processing. Digital signal processing techniques have been deployed to quantify the spectrum compositions of the 20 amino acids. A range of amino acid bar graphs were plotted for comparing cancer cells to non-cancer cells. The results conclude that the cancer cells have higher spectral density values than non-cancer cells.

Keywords: Genomics, signal processing for genomics data, DNA, power spectral density, amino acids, protein

14.1 Introduction

Deoxyribonucleic acid (DNA) clustering analysis innovation has been moving quickly because attempts to find a few hidden gems in the protein-coding sections of DNA have been made for a long time. However, since genetic variation ...