Modeling Protein Synthesis and DNA Mutations using Finite State Machines

Mohammed, Salma; Bourawy, Ashraf Ali

doi:10.1145/3410352.3410773

Cited by 1 publication

(1 citation statement)

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“…At this point, the mutations detected in the DNA sequence are categorized using several classification algorithms based on their influence on the protein structure and function [33]. Based on their consequences, mutations can be divided into the following categories [34], [35]: a) Synonymous mutation: This sort of mutation happens when one of the nucleotides in the code that creates the same amino acid changes, as a result of several genetic codes referring to the same amino acid. − Missense mutation: A missense mutation occurs when one of the nucleotides changes, resulting in the creation of a completely different amino acid from the original amino acid.…”

Section: Dna Mutation Classificationmentioning

confidence: 99%

A survey for the methods of detection and classification of genetic mutations

Saloom

Khafaji

2022

IJEECS

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<span>Research into pathogenic mutations is vital and useful for understanding illness progression, prognosis, and gene-disease connections. Furthermore, pathogenic mutations might have negative implications, such as the development of illnesses or medical problems. In this article, we critically review published studies that are concerned with the detection of genetic mutations and their types using genomic data. Using the reporting items for systematic reviews and meta-analysis criteria, a complete search was conducted on IEEE, Scopus, the Web of Science, Google Scholar, and Elsevier. In our review, we included 73 papers out of a total of more than 150 that were initially discovered. The most common data types used to detect and predict models are deoxyribose nucleic acid (DNA) and protein sequencing data. The examined models have a good level of accuracy. We devised a methodology for developing a detective and predictive model that takes into account all stages of mutation identification and classification.</span>

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Section: Dna Mutation Classificationmentioning

confidence: 99%