FPGA Implementation of DNA Sequence Alignment with Traceback

Sarkar, Ardhendu; Banerjee, Som

doi:10.1109/iceca49313.2020.9297554

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…By matching two biological sequences, pair-wise sequence alignment (PSA) is used to discover the greatest extent of similarity, allowing one to assess the degree of similarity and the potential for homology. Multiple sequence alignment (MSA) is a sort of Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  sequence alignment that involves aligning three or more biological sequences to determine an evolutionary relationship between the query sequences [5]. Since the 1970s, specialists have been extensively studying mutation testing, and significant breakthroughs have been made in terms of ideas, theory, technology, and empirical data.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%