Abstract: Genomic data is used in bioinformatics for collecting, storing and processing the genomes of living things. In order to process the genetic information, machine learning algorithms plays a vital role in building a computational model by using the statistical theory. This paper helps the researchers, who are doing research with the DNA dataset by applying the machine learning logics. Feature scaling machine learning techniques helps in predicting the sequence of genome for extrachromosomal amplification and predicting the tumor intensity in the human gene. Identification of unconventional chromosome in the DNA sequence minimizes the structural risk. In this paper, researchers can get clear insight on classification, sequence prediction, fuzzy relationship and SNP on genome dataset. The performance of various existing models is measured using the performance metrics and the accuracy.

Siripuri Divya, Y. Bhavani and Thota Mahesh Kumar, “A Survey on Genomic Dataset for Predicting the DNA Abnormalities Using Ml” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130537

@article{Divya2022,
title = {A Survey on Genomic Dataset for Predicting the DNA Abnormalities Using Ml},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130537},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130537},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Siripuri Divya and Y. Bhavani and Thota Mahesh Kumar}
}