Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Alkaptonuria (AKU) is an autosomal recessive disorder caused by mutations in the homogentisate-1,2-dioxygenase (HGD) gene leading to the deficiency of HGD enzyme activity. The aim of this study was to use some computational bioinformatics tools to predict the most pathogenic non-synonymous mutations in the HGD gene. The data was retrieved from the SNPs database of the National Center for Biotechnology Information (dbSNPs) (Oct. 2021). The primary sequence of the protein was obtained from the UniProt database (Oct. 2021). The pathogenic effect on the protein structure and function was predicted by GeneMANIA, SIFT, Provean, Polyphen-2, I-Mutant, and Project Hope software. The human HGD gene comprises a total of 423SNPs out of that 348 were found to be synonymous, 75 were missense SNPs (nsSNPs). Analysis of the nsSNPs by SIFT predicts 35 as deleterious and 40 as tolerated ones. Using Provean only 30 were deleterious while 5 SNPs were neutral. Taking the deleterious nsSNPSs to Polyphen-2, 25 nsSNPs were damaging (22 were probably damaging and 3 were possibly damaging), while 5 were benign.
Mona Abdelrahman Mohamed Khaier. 2026. \u201cComputational Analysis of Possibly Pathogenic Non-Synonymous Single Nucleotide Polymorphisms Variants in HGD Gene\u201d. Global Journal of Medical Research - F: Diseases GJMR-F Volume 22 (GJMR Volume 22 Issue F4): .
Crossref Journal DOI 10.17406/gjmra
Print ISSN 0975-5888
e-ISSN 2249-4618
The methods for personal identification and authentication are no exception.
Total Score: 73
Country: Sudan
Subject: Global Journal of Medical Research - F: Diseases
Authors: Mona Abdelrahman Mohamed Khaier, Intisar Hassan Saeed, Mona Abdelrahman Mohamed Khaier (PhD/Dr. count: 0)
View Count (all-time): 113
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Publish Date: 2026 01, Fri
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Alkaptonuria (AKU) is an autosomal recessive disorder caused by mutations in the homogentisate-1,2-dioxygenase (HGD) gene leading to the deficiency of HGD enzyme activity. The aim of this study was to use some computational bioinformatics tools to predict the most pathogenic non-synonymous mutations in the HGD gene. The data was retrieved from the SNPs database of the National Center for Biotechnology Information (dbSNPs) (Oct. 2021). The primary sequence of the protein was obtained from the UniProt database (Oct. 2021). The pathogenic effect on the protein structure and function was predicted by GeneMANIA, SIFT, Provean, Polyphen-2, I-Mutant, and Project Hope software. The human HGD gene comprises a total of 423SNPs out of that 348 were found to be synonymous, 75 were missense SNPs (nsSNPs). Analysis of the nsSNPs by SIFT predicts 35 as deleterious and 40 as tolerated ones. Using Provean only 30 were deleterious while 5 SNPs were neutral. Taking the deleterious nsSNPSs to Polyphen-2, 25 nsSNPs were damaging (22 were probably damaging and 3 were possibly damaging), while 5 were benign.
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