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  • 1
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    Unknown
    Hindawi
    Publication Date: 2014-08-29
    Description: Beta-amyloid precursor protein cleavage enzyme 1 (BACE1) and beta-amyloid precursor protein cleavage enzyme 2 (BACE2), members of aspartyl protease family, are close homologues and have high similarity in their protein crystal structures. However, their enzymatic properties differ leading to disparate clinical consequences. In order to identify the residues that are responsible for such differences, we used evolutionary trace (ET) method to compare the amino acid conservation patterns of BACE1 and BACE2 in several mammalian species. We found that, in BACE1 and BACE2 structures, most of the ligand binding sites are conserved which indicate their enzymatic property of aspartyl protease family members. The other conserved residues are more or less randomly localized in other parts of the structures. Four group-specific residues were identified at the ligand binding site of BACE1 and BACE2. We postulated that these residues would be essential for selectivity of BACE1 and BACE2 biological functions and could be sites of interest for the design of selective inhibitors targeting either BACE1 or BACE2.
    Electronic ISSN: 1537-744X
    Topics: Natural Sciences in General
    Published by Hindawi
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  • 2
    Publication Date: 2014-10-23
    Description: Background: The sequencing of two members of the Royal Kelantan Malay family genomes will provide insights on the Kelantan Malay whole genome sequences. The two Kelantan Malay genomes were analyzed for the SNP markers associated with thalassemia and Helicobacter pylori infection. Helicobacter pylori infection was reported to be low prevalence in the north-east as compared to the west coast of the Peninsular Malaysia and beta-thalassemia was known to be one of the most common inherited and genetic disorder in Malaysia.ResultBy combining SNP information from literatures, GWAS study and NCBI ClinVar, 18 unique SNPs were selected for further analysis. From these 18 SNPs, 10 SNPs came from previous study of Helicobacter pylori infection among Malay patients, 6 SNPs were from NCBI ClinVar and 2 SNPs from GWAS studies. The analysis reveals that both Royal Kelantan Malay genomes shared all the 10 SNPs identified by Maran (Single Nucleotide Polymorphims (SNPs) genotypic profiling of Malay patients with and without Helicobacter pylori infection in Kelantan, 2011) and one SNP from GWAS study. In addition, the analysis also reveals that both Royal Kelantan Malay genomes shared 3 SNP markers; HBG1 (rs1061234), HBB (rs1609812) and BCL11A (rs766432) where all three markers were associated with beta-thalassemia. Conclusions: Our findings suggest that the Royal Kelantan Malays carry the SNPs which are associated with protection to Helicobacter pylori infection. In addition they also carry SNPs which are associated with beta-thalassemia. These findings are in line with the findings by other researchers who conducted studies on thalassemia and Helicobacter pylori infection in the non-royal Malay population.
    Print ISSN: 1877-6558
    Electronic ISSN: 1877-6566
    Topics: Medicine
    Published by SpringerOpen
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  • 3
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    Unknown
    SpringerOpen
    Publication Date: 2014-11-20
    Description: Background: The Malays consist of various sub-ethnic groups which are believed to have different ancestral origins based on their migrations centuries ago. The sub-ethnic groups can be divided based on the region they inhabit; the northern (Melayu Kedah and Melayu Kelantan), western (Melayu Minang) and southern parts (Melayu Bugis and Melayu Jawa) of Peninsular Malaysia. We analyzed 54,794 autosomal single nucleotide polymorphisms (SNPs) which were shared by 472 unrelated individuals from 17 populations to determine the genetic structure and distributions of the ancestral genetic components in five Malay sub-ethnic groups namely Melayu Bugis, Melayu Jawa, Melayu Minang, Melayu Kedah, and Melayu Kelantan. We also have included in the analysis 12 other study populations from Thailand, Indonesia, China, India, Africa and Orang Asli sub-groups in Malay Peninsula, obtained from the Pan Asian SNP Initiative (PASNPI) Consortium and International HapMap project database. Results: We found evidence of genetic influx from Indians to Malays, more in Melayu Kedah and Melayu Kelantan which are genetically different from the other Malay sub-ethnic groups, but similar to Thai Pattani. More than 98% of these northern Malays haplotypes could be found in either Indians or Chinese populations, indicating a highly admixture pattern among populations. Nevertheless, the ancestry lines of Malays, Indonesians and Thais were traced back to have shared a common ancestor with the Proto-Malays and Chinese. Conclusions: These results support genetic admixtures in the Peninsular Malaysia Malay populations and provided valuable information on the enigmatic demographical history as well as shed some insights into the origins of the Malays in the Malay Peninsula.
    Print ISSN: 1877-6558
    Electronic ISSN: 1877-6566
    Topics: Medicine
    Published by SpringerOpen
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  • 4
    Publication Date: 2015-05-01
    Description: Background: The Malaysian Node of the Human Variome Project (MyHVP) is one of the eighteen official Human Variome Project (HVP) country-specific nodes. Since its inception in 9th October 2010, MyHVP has attracted the significant number of Malaysian clinicians and researchers to participate and contribute their data to this project. MyHVP also act as the center of coordination for genotypic and phenotypic variation studies of the Malaysian population. A specialized database was developed to store and manage the data based on genetic variations which also associated with health and disease of Malaysian ethnic groups. This ethnic-specific database is called the Malaysian Node of the Human Variome Project database (MyHVPDb).FindingsCurrently, MyHVPDb provides only information about the genetic variations and mutations found in the Malays. In the near future, it will expand for the other Malaysian ethnics as well. The data sets are specified based on diseases or genetic mutation types which have three main subcategories: Single Nucleotide Polymorphism (SNP), Copy Number Variation (CNV) followed by the mutations which code for the common diseases among Malaysians. MyHVPDb has been open to the local researchers, academicians and students through the registration at the portal of MyHVP (http://hvpmalaysia.kk.usm.my/mhgvc/index.php?id=register). Conclusions: This database would be useful for clinicians and researchers who are interested in doing a study on genomics population and genetic diseases in order to obtain up-to-date and accurate information regarding the population-specific variations and also useful for those in countries with similar ethnic background.
    Electronic ISSN: 1756-0500
    Topics: Biology , Medicine
    Published by BioMed Central
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  • 5
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    Unknown
    BioMed Central
    Publication Date: 2016-06-17
    Description: Fracture healing in bone gap is one of the major challenges encountered in Orthopedic Surgery. At present, the treatment includes bone graft, employing either internal or external fixation which has a signific...
    Electronic ISSN: 1746-6148
    Topics: Medicine
    Published by BioMed Central
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  • 6
    Publication Date: 2017-05-10
    Description: The sequencing of two members of the Royal Kelantan Malay family genomes will provide insights on the Kelantan Malay whole genome sequences. The two Kelantan Malay genomes were analyzed for the SNP markers ass...
    Print ISSN: 1877-6558
    Electronic ISSN: 1877-6566
    Topics: Medicine
    Published by SpringerOpen
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  • 7
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    Unknown
    SpringerOpen
    Publication Date: 2017-05-10
    Description: The Malays consist of various sub-ethnic groups which are believed to have different ancestral origins based on their migrations centuries ago. The sub-ethnic groups can be divided based on the region they inh...
    Print ISSN: 1877-6558
    Electronic ISSN: 1877-6566
    Topics: Medicine
    Published by SpringerOpen
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  • 8
    facet.materialart.
    Unknown
    SpringerOpen
    Publication Date: 2016-01-15
    Description: The Malays consist of various sub-ethnic groups which are believed to have different ancestral origins based on their migrations centuries ago. The sub-ethnic groups can be divided based on the region they inh...
    Print ISSN: 1877-6558
    Electronic ISSN: 1877-6566
    Topics: Medicine
    Published by SpringerOpen
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  • 9
    Publication Date: 2016-01-15
    Description: The sequencing of two members of the Royal Kelantan Malay family genomes will provide insights on the Kelantan Malay whole genome sequences. The two Kelantan Malay genomes were analyzed for the SNP markers ass...
    Print ISSN: 1877-6558
    Electronic ISSN: 1877-6566
    Topics: Medicine
    Published by SpringerOpen
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  • 10
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    Unknown
    BioMed Central
    Publication Date: 2013-06-01
    Description: Background: Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results: In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions: The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies.
    Electronic ISSN: 1471-2105
    Topics: Biology , Computer Science
    Published by BioMed Central
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