• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.269-277
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• 2012

In microarray data analysis, recent efforts have focused on the discovery of gene sets from a pathway or functional categories such as Gene Ontology terms(GO terms) rather than on individual gene function for its direct interpretation of genome-wide expression data. We introduce a meta-analysis method that combines $p$-values for changes of each gene in the group. The method measures the significance of overall treatment-induced change in a gene group. An application of the method to a real data demonstrates that it has benefits over other statistical methods such as Fisher's exact test and permutation methods. The method is implemented in a SAS program and it is available on the author's homepage(http://cafe.daum.net/go.analysis).

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.47-56
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• 2018

The aim of this study is investigate the research trends by analyzing the researches related to Korean and international genetics in oncology nursing. We conducted a text network analysis focusing on the key words presented in the abstracts of papers published in journals related to genetics in oncology nursing. Nurse, Cancer, Genetic, Patient, Knowledge, Care, and Genetic Test were identified as keywords and centralized keywords. As a result of studying research trends over time, researches including keywords such as information, care, and knowledge have increased since the completion of the Human Genome Project in 2003. Key words classified through the meta paradigm of nursing were health, nursing, human, environment order. This study is meaningful in that it can be used to identify trends in tumor genetic nursing research and to set the direction of development of nursing intervention for hereditary cancer patients.

• The Korean Journal of Physiology and Pharmacology
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• v.21 no.3
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• pp.353-360
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• 2017

Several human diseases have been associated with mitochondrial voltage-dependent anion channel-1 (VDAC1) due to its role in calcium ion transportation and apoptosis. Recent studies suggest that VDAC1 may interact with endothelium-dependent nitric oxide synthase (eNOS). Decreased VDAC1 expression may limit the physical interaction between VDAC1 and eNOS and thus impair nitric oxide production, leading to cardiovascular diseases, including pulmonary arterial hypertension (PAH). In this report, we conducted meta-analysis of genome-wide expression data to identify VDAC1 influenced genes implicated in PAH pathobiology. First, we identified the genes differentially expressed between wild-type and Vdac1 knockout mouse embryonic fibroblasts in hypoxic conditions. These genes were deemed to be influenced by VDAC1 deficiency. Gene ontology analysis indicates that the VDAC1 influenced genes are significantly associated with PAH pathobiology. Second, a molecular signature derived from the VDAC1 influenced genes was developed. We suggest that, VDAC1 has a protective role in PAH and the gene expression signature of VDAC1 influenced genes can be used to i) predict severity of pulmonary hypertension secondary to pulmonary diseases, ii) differentiate idiopathic pulmonary artery hypertension (IPAH) patients from controls, and iii) differentiate IPAH from connective tissue disease associated PAH.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.101-119
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• 2003

Achieving the beneficiary goal of recent discovery in human genome project still needs a way to retrieve and analyze the exponentially expanding bio-related information. Research on bio-related fields naturally applies knowledge discovered to the current problem and make inferences to extract new information where shared concepts and data containing information need to be defined and used in a coherent way. In such a professional domain, while the need to help users reduce their work and to improve search results has been emerged, methods for systematic retrieval and adequate exchange of relevant information are still in their infancy. The design of our system aims at improving the quality of information retrieval in a professional domain by utilizing both corpus-based and concept-based ontology. Meta-rules of helping users to make an adequate query are formed into an ontology in the domain. The integration of those knowledge permits the system to retrieve relevant information in a more semantic and systematic fashion. This work mainly describes the query models with details of GUI and a secondary query generation of the system.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.1-7
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• 2018

Feature selection, one of data preprocessing techniques, is one of major research areas in many applications dealing with large dataset. It has been used in pattern recognition, machine learning and data mining, and is now widely applied in a variety of fields such as text classification, image retrieval, intrusion detection and genome analysis. The proposed method is based on a genetic algorithm which is one of meta-heuristic algorithms. There are two methods of finding feature subsets: a filter method and a wrapper method. In this study, we use a wrapper method, which evaluates feature subsets using a real classifier, to find an optimal feature subset. The training dataset used in the experiment has a severe class imbalance and it is difficult to improve classification performance for rare classes. After preprocessing the training dataset with SMOTE, we select features and evaluate them with various machine learning algorithms.

• Korean Journal of Schizophrenia Research
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• v.21 no.2
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• pp.43-50
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• 2018

Objectives : Genome-wide association studies (GWASs) and meta-analyses indicate that single-nucleotide polymorphisms (SNPs) in the a-1C subunit of the L-type voltage-dependent calcium channel (CACNA1C) gene increase the risk for schizophrenia and bipolar disorders (BDs). We investigated the association between the genetic variants on CACNA1C and schizophrenia and/or BDs in the Korean population. Methods : A total of 582 patients with schizophrenia, 336 patients with BDs consisting of 179 bipolar I disorder (BD-I) and 157 bipolar II disorder (BD-II), and 502 healthy controls were recruited. Based on previous results from other populations, three SNPs (rs10848635, rs1006737, and rs4765905) were selected and genotype-wise association was evaluated using logistic regression analysis under additive, dominant and recessive genetic models. Results : rs10848635 showed a significant association with schizophrenia (p=0.010), the combined schizophrenia and BD group (p=0.018), and the combined schizophrenia and BD-I group (p=0.011). The best fit model was dominant model for all of these phenotypes. The association remained significant after correction for multiple testing in schizophrenia and the combined schizophrenia and BD-I group. Conclusion : We identified a possible role of CACNA1C in the common susceptibility of schizophrenia and BD-I. However no association trend was observed for BD-II. Further efforts are needed to identify a specific phenotype associated with this gene crossing the current diagnostic categories.