• Genomics & Informatics
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• v.11 no.1
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• pp.15-23
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• 2013

CD8+T cells are key factors mediating hepatitis B virus (HBV) clearance. However, these cells are killed through HBV-induced apoptosis during the antigen-presenting period in HBV-induced chronic liver disease (CLD) patients. Interferon-inducible protein 6 (IFI6) delays type I interferon-induced apoptosis in cells. We hypothesized that single nucleotide polymorphisms (SNPs) in the IFI6 could affect the chronicity of CLD. The present study included a discovery stage, in which 195 CLD patients, including chronic hepatitis B (HEP) and cirrhosis patients and 107 spontaneous recovery (SR) controls, were analyzed. The genotype distributions of rs2808426 (C > T) and rs10902662 (C > T) were significantly different between the SR and HEP groups (odds ratio [OR], 6.60; 95% confidence interval [CI], 1.64 to 26.52, p = 0.008 for both SNPs) and between the SR and CLD groups (OR, 4.38; 95% CI, 1.25 to 15.26; p = 0.021 and OR, 4.12; 95% CI, 1.18 to 14.44; p = 0.027, respectively). The distribution of diplotypes that contained these SNPs was significantly different between the SR and HEP groups (OR, 6.58; 95% CI, 1.63 to 25.59; p = 0.008 and OR, 0.15; 95% CI, 0.04 to 0.61; p = 0.008, respectively) and between the SR and CLD groups (OR, 4.38; 95% CI, 1.25 to 15.26; p = 0.021 and OR, 4.12; 95% CI, 1.18 to 14.44; p = 0.027, respectively). We were unable to replicate the association shown by secondary enrolled samples. A large-scale validation study should be performed to confirm the association between IFI6 and HBV clearance.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3663-3667
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• 2012

The hepatitis B virus (HBV) and the hepatitis C virus (HCV) are still public health problems in Yemen, with older individuals having much higher prevalence than younger generations. However, research on the prevalence of viral hepatitis in association with hepatocellular cancer (HCC) has not yet been undertaken in Yemen. The aim of this study was to determine the prevalence of HBV and HCV infection among HCC patients and to estimate the risk of these infections being associated with the development of HCC. A cross-sectional study was conducted on patients attending oncology outpatient in Sana'a, Yemen, through the period 2008-mid 2010 with confirmed diagnosis of HCC. A total of 88 cases were studied thoroughly with different investigations such as CT-scan, ultrasound, tumour marker, alpha-feto-protein and histopathological biopsy. A structured questionnaire was also applied and physical examination done to assess the general condition of the patients. Statistical package (SPSS version 16) was used for analysis of the data. The mean age of the cases was 61.2 years (${\pm}12.6$) with half over 60 years. There were fewer male patients (36%) compared to females and most (97%) only had basic /no formal education. Seventy nine (89%) were diagnosed as HCC cases with histopathological biopsy while the rest were diagnosed by ultrasound, CT scan, tumour marker, and alpha-feto-protein. Around one-third of the subjects were positive for HBsAg and HCV antibodies. Multivariate analysis showed infection with HCV and use of smoking was associated with HCC diagnosis. Although an association was observed between the occurrence of HCC and viral hepatitis (either HBV or HCV) and cigarette smoking, but the rate of viral infection was lower than what has been reported elsewhere.

• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• Genomics & Informatics
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• v.10 no.3
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• pp.167-174
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• 2012

AKT is a signal transduction protein that plays a central role in the tumorigenesis. There are 3 mammalian isoforms of this serine/threonine protein kinase-AKT1, AKT2, and AKT3-showing a broad tissue distribution. We first discovered 2 novel polymorphisms (AKT2 -9826 C/G and AKT3 -811 A/G), and we confirmed 6 known polymorphisms (AKT2 -9473 C/T, AKT2 -9151 C/T, AKT2 -9025 C/T, AKT2 -8618G/A, AKT3 -675 A/-, and AKT3 -244 C/T) of the AKT2 and AKT3 promoter region in 24 blood samples of Korean lung cancer patients using direct sequencing. To evaluate the role of AKT2 and AKT3 polymorphisms in the risk of Korean lung cancer, genotypes of the AKT2 and AKT3 polymorphisms (AKT2 -9826 C/G, AKT2 -9473 C/T, AKT2 -9151 C/T, AKT2 -9025 C/T, AKT2 -8618G/A, and AKT3 -675 A/-) were determined in 360 lung cancer patients and 360 normal controls. Statistical analyses revealed that the genotypes and haplotypes in the AKT2 and AKT3 promoter regions were not significantly associated with the risk of lung cancer in the Korean population. These results suggest that polymorphisms of the AKT2 and AKT3 promoter regions do not contribute to the genetic susceptibility to lung cancer in the Korean population.

• Genomics & Informatics
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• v.4 no.3
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• pp.97-102
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• 2006

In acute leukemia patients, several successful methods of expression profiling have been used for various purposes, i.e., to identify new disease class, to select a therapeutic target, or to predict chemo-sensitivity and clinical outcome. In the present study, we tested the peripheral blood of 47 acute leukemia patients in an attempt to identify differentially expressed genes in AML and ALL using a Korean-made 10K oligo-nucleotide microarray. Methods: Total RNA was prepared from peripheral blood and amplified for microarray experimentation. SAM (significant analysis of microarray) and PAM (prediction analysis of microarray) were used to select significant genes. The selected genes were tested for in a test group, independently of the training group. Results: We identified 345 differentially expressed genes that differentiated AML and ALL patients (FWER<0.05). Genes were selected using the training group (n=35) and tested for in the test group (n=12). Both training group and test group discriminated AML and ALL patients accurately. Genes that showed relatively high expression in AML patients were deoxynucleotidyl transferase, pre-B lymphocyte gene 3, B-cell linker, CD9 antigen, lymphoid enhancer-binding factor 1, CD79B antigen, and early B-cell factor. Genes highly expressed in ALL patients were annexin A 1, amyloid beta (A4) precursor protein, amyloid beta (A4) precursor-like protein 2, cathepsin C, lysozyme (renal amyloidosis), myeloperoxidase, and hematopoietic prostaglandin D2 synthase. Conclusion: This study provided genome wide molecular signatures of Korean acute leukemia patients, which clearly identify AML and ALL. Given with other reported signatures, these molecular signatures provide a means of achieving a molecular diagnosis in Korean acute leukemia patents.

• Genomics & Informatics
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• v.2 no.2
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• pp.67-74
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• 2004

Cells consistently face stressful conditions, which cause them to modulate a variety of intracellular processes and adapt to these environmental changes via regulation of gene expression. Hyperosmotic and oxidative stresses are significant stressors that induce cellular damage, and finally cell death. In this study, oligonucleotide microarrays were employed to investigate mRNA level changes in cells exposed to hyperosmotic or oxidative conditions. In addition, since heat shock protein 70 (HSP70) is one of the most inducible stress proteins and plays pivotal role to protect cells against stressful condition, we performed microarray analysis in HSP70-overexpressing cells to identify the genes expressed in a HSP70-dependent manner. Under hyperosmotic or oxidative stress conditions, a variety of genes showed altered expression. Down­regulation of protein phosphatase1 beta (PP1 beta) and sphingosine-1-phosphate phosphatase 1 (SPPase1) was detected in both stress conditions. Microarray analysis of HSP70-overexpressing cells demonstrated that diverse mRNA species depend on the level of cellular HSP70. Genes encoding Iysyl oxidase, thrombospondin 1, and procollagen displayed altered expression in all tested conditions. The results of this study will be useful to construct networks of stress response genes.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Genomics & Informatics
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• v.12 no.2
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• pp.58-63
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• 2014

The tyrosine-protein kinase Tec (TEC) is a member of non-receptor tyrosine kinases and has critical roles in cell signaling transmission, calcium mobilization, gene expression, and transformation. TEC is also involved in various immune responses, such as mast cell activation. Therefore, we hypothesized that TEC polymorphisms might be involved in aspirin-exacerbated respiratory disease (AERD) pathogenesis. We genotyped 38 TEC single nucleotide polymorphisms in a total of 592 subjects, which comprised 163 AERD cases and 429 aspirin-tolerant asthma controls. Logistic regression analysis was performed to examine the associations between TEC polymorphisms and the risk of AERD in a Korean population. The results revealed that TEC polymorphisms and major haplotypes were not associated with the risk of AERD. In another regression analysis for the fall rate of forced expiratory volume in 1 second ($FEV_1$) by aspirin provocation, two variations (rs7664091 and rs12500534) and one haplotype (TEC_BL2_ht4) showed nominal associations with $FEV_1$ decline (p=0.03-0.04). However, the association signals were not retained after performing corrections for multiple testing. Despite TEC playing an important role in immune responses, the results from the present study suggest that TEC polymorphisms do not affect AERD susceptibility. Findings from the present study might contribute to the genetic etiology of AERD pathogenesis.

• Genomics & Informatics
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• v.14 no.3
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• pp.96-103
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• 2016

The influenza A (H1N1) virus, also known as swine flu is a leading cause of morbidity and mortality since 2009. There is a need to explore novel anti-viral drugs for overcoming the epidemics. Traditionally, different plant extracts of garlic, ginger, kalmegh, ajwain, green tea, turmeric, menthe, tulsi, etc. have been used as hopeful source of prevention and treatment of human influenza. The H1N1 virus contains an important glycoprotein, known as neuraminidase (NA) that is mainly responsible for initiation of viral infection and is essential for the life cycle of H1N1. It is responsible for sialic acid cleavage from glycans of the infected cell. We employed amino acid sequence of H1N1 NA to predict the tertiary structure using Phyre2 server and validated using ProCheck, ProSA, ProQ, and ERRAT server. Further, the modelled structure was docked with thirteen natural compounds of plant origin using AutoDock4.2. Most of the natural compounds showed effective inhibitory activity against H1N1 NA in binding condition. This study also highlights interaction of these natural inhibitors with amino residues of NA protein. Furthermore, among 13 natural compounds, theaflavin, found in green tea, was observed to inhibit H1N1 NA proteins strongly supported by lowest docking energy. Hence, it may be of interest to consider theaflavin for further in vitro and in vivo evaluation.

• Genomics & Informatics
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• v.14 no.2
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• pp.53-61
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• 2016

Toxoplasma gondii is an intracellular Apicomplexan parasite and a causative agent of toxoplasmosis in human. It causes encephalitis, uveitis, chorioretinitis, and congenital infection. T. gondii invades the host cell by forming a moving junction (MJ) complex. This complex formation is initiated by intermolecular interactions between the two secretory parasitic proteins-namely, apical membrane antigen 1 (AMA1) and rhoptry neck protein 2 (RON2) and is critically essential for the host invasion process. By this study, we propose two potential leads, NSC95522 and NSC179676 that can efficiently target the AMA1 hydrophobic cleft, which is a hotspot for targeting MJ complex formation. The proposed leads are the result of an exhaustive conformational search-based virtual screen with multilevel precision scoring of the docking affinities. These two compounds surpassed all the precision levels of docking and also the stringent post docking and cumulative molecular dynamics evaluations. Moreover, the backbone flexibility of hotspot residues in the hydrophobic cleft, which has been previously reported to be essential for accommodative binding of RON2 to AMA1, was also highly perturbed by these compounds. Furthermore, binding free energy calculations of these two compounds also revealed a significant affinity to AMA1. Machine learning approaches also predicted these two compounds to possess more relevant activities. Hence, these two leads, NSC95522 and NSC179676, may prove to be potential inhibitors targeting AMA1-RON2 complex formation towards combating toxoplasmosis.