DNA Sequencing Using Machine Learning Algorithms | IEEE Conference Publication | IEEE Xplore

DNA Sequencing Using Machine Learning Algorithms


Abstract:

A genome consists of the genetic information of the organism. Sequencing thousands and millions of DNA molecules in a human individual gives the doctor the information ab...Show More

Abstract:

A genome consists of the genetic information of the organism. Sequencing thousands and millions of DNA molecules in a human individual gives the doctor the information about the genetic makeup that is the genetic information carried out in the human body. This method plays a vital role in determining the variations and mutations within a specific genetic disease. Researchers and doctors use this piece of information to more fully understand the patient’s current health status and help them to make a future plan for treatment and operations. DNA sequencing is done to track epidemics, learn about the past portfolio of the individual and find better treatments for life threatening diseases like Cancer and arthritis. Understanding a patient’s unique genetic profile can allow drug makers to target specific subgroups of individuals grouped together by similar genetic makeup. This can result in more exact and tailored information such as in the medication type itself down to the dosage level. Hence DNA sequencing plays an integral role in the biomedical research process. In this project we will be using different Machine learning techniques like SVM, CNN, LSTM, Random forest classifier, Adaboost, naive bayes, SVM, KNN to sequence the DNA on a human dataset, this study analysis can aid us understand and conclude which algorithm works better and can give a satisfying accuracy.
Date of Conference: 08-10 December 2022
Date Added to IEEE Xplore: 02 February 2023
ISBN Information:
Conference Location: Chennai, India

References

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