• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.547-554
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• 2021

Cancer patients can have different kinds of cancer driver genes, and identification of these patient-specific cancer driver genes is an important step in the development of personalized cancer treatment and drug development. Several bioinformatic methods have been proposed for this purpose, but there is room for improvement in terms of accuracy. In this paper, we propose NPD (Network based Patient-specific Driver gene identification) for identifying patient-specific cancer driver genes. NPD consists of three steps, constructing a patient-specific gene network, applying the modified PageRank algorithm to assign scores to genes, and identifying cancer driver genes through a score comparison method. We applied NPD on six cancer types of TCGA data, and found that NPD showed generally higher F1 score compared to existing patient-specific cancer driver gene identification methods.

• Journal of Korean geriatric psychiatry
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• v.16 no.1
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• pp.17-23
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• 2012

The diagnosis of Alzheimer's disease (AD) is still obscure even to specialists. To improve the diagnostic accuracy, to find at-risk people as early as possible, to predict the efficacy or adverse reactions of pharmacotherapy on an individual basis, to attain more reliable results of clinical trials by recruiting better defined participants, to prove the disease-modifying ability of new candidate drugs, to establish prognosis-based therapeutic plans, and to do more, is now increasing the need for biomarkers for AD. Among AD-related biochemical markers, cerebrospinal beta-amyloid and tau have been paid the most attention since they are materials directly interfacing the brain interstitium and can be obtained through the lumbar puncture. Level of beta-amyloid is reduced whereas tau is increased in cerebrospinal fluid of AD patients relative to cognitively normal elderly people. Remarkably, such information has been found to help predict AD conversion of mild cognitive impairment. Despite inconsistent findings from previous studies, plasma beta-amyloid is thought to be increased before the disease onset, but show decreasing change as the disease progress. Regarding other peripheral biochemical markers, omics tools are being widely used not only to find useful biomarkers but also to generate novel hypotheses for AD pathogenesis and to lead new personalized future medicine.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.75-84
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• 2014

In this paper, we dealt with feature selection problem of large-scale and high-dimensional biological data such as omics data. For this problem, most of the previous approaches used simple score function to reduce the number of original variables and selected features from the small number of remained variables. In the case of methods that do not rely on filtering techniques, they do not consider the interactions between the variables, or generate approximate solutions to the simplified problem. Unlike them, by combining set covering and clustering techniques, we developed a new method that could deal with total number of variables and consider the combinatorial effects of variables for selecting good features. To demonstrate the efficacy and effectiveness of the method, we downloaded gene expression datasets from TCGA (The Cancer Genome Atlas) and compared our method with other algorithms including WEKA embeded feature selection algorithms. In the experimental results, we showed that our method could select high quality features for constructing more accurate classifiers than other feature selection algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1655-1661
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• 2007

Recently, various industries have appeared which are applied ubiquitous technology. Particularly, health and medical fields, have been focused as future's industry, have been combined with ubiquitous system. This is what we called' u-Health industry. Korean government has encouraged local governments to develop specialized high value-added industries along each local's circumstance. According to the policy, I had an assumption that u-Health industry is Chungbuk province's specialized high value-added industry and studied marketing strategy for the point of penetration into markets. I presented STP strategy for international markets. This strategy referred to developed countries' aging index and based on Modigliani's life cycle hypothesis. Finally, considering none of u-Health has been released, I presented strategies of marketing mix to be utilized when u-Health items march into the markets.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.11
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• pp.93-100
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• 2005

In this paper, we implement the embedded speech recognition system to support various application services such as audio and video control using speech recognition interface on cars. The embedded speech recognition system is implemented and ported in a DSP board. Because MIC type and speech codecs affect the accuracy of speech recognition. And also, we optimize the simulation and test environment to effectively remove the real noises on a car. We applied a noise suppression and feature compensation algorithm to increase an accuracy of sppech recognition on a car. And we used a context dependent tied-mixture acoustic modeling. The performance evaluation showed high accuracy of proposed system in office environment and even real car environment.

• Journal of Plant Biotechnology
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• v.37 no.1
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• pp.12-24
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• 2010

Plant metabolomics is a research field for identifying all of the metabolites found in a certain plant cell, tissue, organ, or whole plant in a given time and conditions and for studying changes in metabolic profiling as time goes or conditions change. Metabolomics is one of the most recently developed omics for holistic approach to biology and is a kind of systems biology. Metabolomics or metabolite fingerprinting techniques usually involves collecting spectra of crude solvent extracts without purification and separation of pure compounds or not in standardized conditions. Therefore, that requires a high degree of reproducibility, which can be achieved by using a standardized method for sample preparation and data acquisition and analysis. In plant biology, metabolomics is applied for various research fields including rapid discrimination between plant species, cultivar and GM plants, metabolic evaluation of commercial food stocks and medicinal herbs, understanding various physiological, stress responses, and determination of gene functions. Recently, plant metabolomics is applied for characterization of gene function often in combination with transcriptomics by analyzing tagged mutants of the model plants of Arabidopsis and rice. The use of plant metabolomics combined by transcriptomics in functional genomics will be the challenge for the coming year. This review paper attempted to introduce current status and prospects of plant metabolomics research.

• Journal of Life Science
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• v.28 no.10
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• pp.1244-1253
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• 2018

Rumen microbiome consists of a wide variety of microorganisms, such as bacteria, archaea, protozoa, fungi, and viruses, that are in a symbiotic relationship in a strict anaerobic environment in the rumen. These rumen microbiome, a vital maker, play a significant role in feed fermentation within the rumen and produce different volatile fatty acids (VFAs). VFAs are essential for energy metabolism and protein synthesis of the host animal, even though emission of methane gas after feed fermentation is considered a negative indicator of loss of dietary energy of the host animal. To improve rumen microbial efficiency, a variety of approaches, such as feed formulation, the addition of natural feed additives, dietary feed-microbes, etc., have taken to increase ruminant performance. Recently with the application of high-throughput sequencing or next-generation sequencing technologies, especially for metagenomics and metatranscriptomics of rumen microbiomes, our understanding of rumen microbial diversity and function has significantly increased. The metaproteome and metabolome provide deeper insights into the complicated microbial network of the rumen ecosystem and its response to different ruminant diets to improve efficiency in animal production. This review summarized some recent advances of rumen microbiome techniques, especially "meta-omics," viz. metagenomic, metatranscriptomic, metaproteomic, and metabolomic techniques to increase feed fermentation and utilization in ruminants.

• Proceedings of the Korea Association of Crystal Growth Conference
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• 1996.06b
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• pp.259-279
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• 1996

최근 정보·전자산업의 발전으로 고 신뢰성 전자재료에 대한 수요가 증대되고 있으며 이러한 첨단산업의 기반의 될 신소재 중 전자세라믹스가 차지하는 비중이 그 대부분을 차지하고 있으며 이에 대한 수요와 기대가 점점 커지고 있다. 이러한 전자세라믹스는 유전재료, 자성재료, 압전재료, 도전성 재료 등으로 나뉘게 된다. 어떠한 분류에 들어가든 그 조성은 금속의 산화물 형태가 일반적이며 미세한 분말의 성형체를 소결(sintering) 함으로써 최종제품으로 완성된다. 이러한 전잣라믹스가 최근 요구되는 고 신뢰성, 고 밀도화를 달성하기 위해선 원료 분말 제조단계부터 제어가 필요하다. 원료분말의 균일·균질성과 그 입도는 소결특성 뿐만아니라 전기적 특성에도 큰 영향을 미치기 때문이다. 세라믹스의 분말제조 방법 중 일반적으로 사용되는 방법으로는 고상 산화물을 혼합하여 하소(calcination)한 후 분쇄하는 '고상합성법'과 금속의 염 또는 alkoxide 용액을 이용하여 화학적으로 제조하는 '습식 화학적 합성법'이 있다. 고상합성법은 합성온도가 높고 기계적 분쇄와 혼합에 의존하므로 균일·균질성이 떨어지고 분말크기를 1㎛ 이하로 만들기 힘들다. 반면에 습식화학적 합성법은 기계적인 분쇄와 혼합에선 얻을 수 없는 원자 혹은 분자단위의 균일한 혼합과 submicron 이하의 미세한 분말을 얻을 수 있다. 따라서 이러한 습식 화학적 합성으로 얻은 분말을 사용하면 미세한 입자의 특성으로 인해 소결온도를 낮출 수 있으며 균일한 미세구조와 균질한 조성을 갖게되어 기계적·전기적 물성증진도 가져올 수 있게 된다. 습식 화학적 분말합성법은 전술하였듯이 alkoxide의 가수분해를 이용하는 sol-gel 법과 금속의 염(salt) 용액을 이용하여, 화학적으로 화합물 침전을 얻거나 또는 공침전물(coprecipitate) 형태의 분말을 얻는, 침전법으로 나뉠 수 있다. 침전법의 근본원리는 pH 및 pCO3 등에 따른 이온종의 용해도 차이를 이용하는 것으로써 각 이온종에 따른 solubility product(ksp)를 이용하여 설명된다. 본 연구에서는 침전법을 사용한 Ba-, Pb-계 전자세라믹스의 분말합성에 대한 이론적 고찰과 공정개발 및 실험을 통한 물성증진 효과에 대해 알아보았다. 본 실험상의 전자세라믹스 조성은 강유전체, 세라믹반도체, 압효과에 대해 알아보았다. 본 실험상의 전자세라믹스 조성은 강유전체, 세라믹 반도체, 압전재료로 널리 사용되는 BaTiO3, PZT(PbZrO3-PbTiO3)와 수직 자기기록매체로 큰 가능성이 있으며 hard ferrite로 널리쓰이는 Ba-feerite(BaFe12O19)로써 수산화물 형태의 침전에 대한 기구(mechanism)와 물성에 대해 살펴보았다. 이러한 침전법에 의한 분말합성 과정에는 소결체의 물성에 영향을 미치는 pH 조절제나 원료에서 혼입될 수 있는 Na+, K+, Cl-, SO4- 등의 제거(washing 혹은 filtering)가 필수적이다. 그러나 침전법에서 얻게 되는 분말은 매우 미세하여 colloid를 형성하게 되며, 이러한 colloid 상태의 미세한 침전입자가 filtering media에 끼이게 되어 견고하면서도 상당한 부피를 가지는 filter cake을 형성하기 때문에 filtering에 많은 시간과 다량의 filtering agent (본 실험의 경우엔 증류수)가 필요하게 된다. 따라서 이러한 문제점을 해결하기 위하여 colloid 상태의 침전물을 얼렸다 녹이는 freezing process를 개발, 적용하여 그 원리 및 효과, 그로인한 분말형태를 관찰하여 보았다.

• Journal of Plant Biotechnology
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• v.39 no.1
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• pp.33-48
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• 2012

As a scientific curiosity to understand the structure and the function of crops and experimental efforts to apply it to plant breeding, genetic maps have been constructed in various crops. Especially, in the case of Brassica crop, genetic mapping has been accelerated since genetic information of model plant $Arabidopsis$ was available. As a result, the whole $B.$ $rapa$ genome (A genome) sequencing has recently been done. The genome sequences offer opportunities to develop molecular markers for genetic analysis in $Brassica$ crops. RFLP markers are widely used as the basis for genetic map construction, but detection system is inefficiency. The technical efficiency and analysis speed of the PCR-based markers become more preferable for many form of $Brassica$ genome study. The massive sequence informative markers such as SSR, SNP and InDels are also available to increase the density of markers for high-resolution genetic analysis. The high density maps are invaluable resources for QTLs analysis, marker assisted selection (MAS), map-based cloning and comparative analysis within $Brassica$ as well as related crop species. Additionally, the advents of new technology, next-generation technique, have served as a momentum for molecular breeding. Here we summarize genetic and genomic resources and suggest their applications for the molecular breeding in $Brassica$ crop.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.