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Iranian Journal of Biotechnology، جلد ۲۲، شماره ۲، صفحات ۱۱۰-۱۱۷
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عنوان انگلیسی In-Silico Method for Predicting Pathogenic Missense Variants Using Online Tools: AURKA Gene A as a Model
چکیده انگلیسی مقاله Background: In-silico analysis provides a fast, simple, and cost-free method for identifying potentially pathogenic single 
nucleotide variants. 
Objective: To propose a simple and relatively fast method for the prediction of variant pathogenicity using free online 
in-silico (IS) tools with AURKA gene as a model.
Materials and Methods: We aim to propose a methodology to predict variants with high pathogenic potential using 
computational analysis, using AURKA gene as model. We predicted a protein model and analyzed 209 out of 64,369 
AURKA variants obtained from Ensembl database. We used bioinformatic tools to predict pathogenicity. The results were 
compared through the VarSome website, which includes its own pathogenicity score and the American College of Medical Genetics (ACMG) classification.
Results: Out of the 209 analyzed variants, 16 were considered pathogenic, and 13 were located in the catalytic domain. 
The most frequent protein changes were size and hydrophobicity modifications of amino acids. Proline and Glycine amino 
acid substitutions were the most frequent changes predicted as pathogenic. These bioinformatic tools predicted functional changes, such as protein up or down-regulation, gain or loss of molecule interactions, and structural protein modifications. When compared to the ACMG classification, 10 out of 16 variants were considered likely pathogenic, with 7 out of 10 changes at Proline/Glycine substitutions.
Conclusion: This method allows quick and cost-free bulk variant screening to identify variants with pathogenic potential 
for further association and/or functional studies. 
کلیدواژه‌های انگلیسی مقاله Computational Biology,Genomic Structural Variation,Missense Mutation,Single nucleotide polymorphism
نویسندگان مقاله Eric Jonathan Maciel-Cruz |
Doctorado en Genética Humana, Instituto de Genética Humana “Dr. Enrique Corona Rivera”, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara (UdG), Guadalajara, Jalisco, México

Luis Eduardo Figuera-Villanueva |
1 Doctorado en Genética Humana, Instituto de Genética Humana “Dr. Enrique Corona Rivera”, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara (UdG), Guadalajara, Jalisco, México

Liliana Gómez-Flores-Ramos |
CONAHCYT- Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico.

Rubiceli Hernández-Peña |
Doctorado en Genética Humana, Instituto de Genética Humana “Dr. Enrique Corona Rivera”, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara (UdG), Guadalajara, Jalisco, México

Martha Patricia Gallegos-Arreola |
División de Genética, Centro de Investigación Biomédica de Occidente (CIBO), Instituto Mexicano del Seguro Social (IMSS), Guadalajara, Jalisco, México

نشانی اینترنتی https://www.ijbiotech.com/article_196871_799543b81847e8398e9dacb795634c4c.pdf
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