• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.295-297
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• 2001

최근 생물 유전자 정보를 효과적으로 분석하기 위한 적절한 도구의 필요성이 대두되고 있다. 본 논문에서는 백혈병 환자의 골수로부터 얻어낸 DNA Microarray 유전 정보를 분류하여 환자가 가지고 있는 암의 종류를 예측하기 위한 최적의 특징추출방법과 분류 방법을 찾고자 한다. 이를 위해 피어슨 상관관계, 유클리디안 거리, 코사인 계수, 스피어맨 상관관계, 정보 이득, 상호 정보, 신호 대잡음비의 7가지 특징 추출 방법을 사용하였으며, 역전과 신경망, 의사결정 트리, 구조 적응형 자기구성 지도, $textsc{k}$-최근접 이웃 등 가지의 기계학습 분류기를 이용하여 분류 실험을 하였다. 실험결과, 피어슨 상관관계와 역전파 신경망을 이용한 분류 방법이 97.1%의 인식률을 보임을 알 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.10
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• pp.677-684
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• 2015

It is often necessary to predict the vibration patterns of the structures from the signals of finite number of vibration sensors. This study presents the optimal placement of vibration sensors by applying the genetic algorithm and the modal expansion method. The modal expansion method is used to estimate the vibration response of the whole structure. The genetic algorithm is used to estimate the optimal placement of vibration sensors. Optimal sensor placement can be obtained so that the fitness function is minimized in the genetic algorithm. This paper discusses the comparison of the performances of two types of fitness functions, modal assurance criteria(MAC) and condition number( CN). As a result, the estimation using MAC shows better performance than using CN.

• Journal of Life Science
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• v.18 no.7
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• pp.1011-1014
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• 2008

The ability or inability to taste phenylthiocarbamide (PTC) is a classic inherited trait that has been best-studied in human populations. Also, variation in PTC perception has been correlated with dietary preferences and thus may have important consequence for diet-related diseases in modem populations. The recent identification of the TAS2R38 gene (PTC gene) which is a member of TAS2R family of bitter taste receptor genes and three common polymorphisms in the gene is highly correlated with taste sensitivity to PTC. Balancing natural selection has acted to maintain high frequency of both alleles of the gene in human population. Future detailed studies of the relationships between molecular mechanisms and taste function may have therapeutic implications, such as helping patients to consume beneficial bitter-tasting compounds.

• The korean journal of orthodontics
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• v.33 no.3 s.98
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• pp.185-197
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• 2003

This study was performed to identify the characteristics of the OFC1 gene (locus: chromosome 6p24.3) in Korean patients, which is assumed to be the major gene behind the nonsyndromic cleft lip and palate. The sample consisted of 80 subjects: 40 nonsyndromic cleft lip and palate patients (proband, 20 males and females, mean age 14.2 years); and 40 normal adults (20 males and 20 females, mean age 25.6 years). Using PCR-based assay, the OFC1 gene was amplified, sequenced, and then searched for similar protein structures. Results were as follows: 1. The OFC1 gene contains the microsatellite marker 'CA' repeats. The number of the reference 'CA' repeats was 21 times, and formed as TA(CA)11TA(CA)10. But, in Koreans, the number of tandem 'CA' repeats was varied from 17 to 26 except 18, and 'CA' repeats consisted of TA(CA)n. 2. Nine allelic variants were found. Distribution of the OFC1 allele was similar between the patients and control group. 3. There was a replacement of the base 'T' to 'C' after 11 tandem 'CA' repeats in Koreans compared with Weissenbach's report. However, the difference did not seem to be the ORF prediction results between Koreans and Weissenbach's report. 4. The BLAST search results showed the Telomerase reverse transcriptase (TERT) and the Nucleotide binding protein 2 (NBP2) as similar proteins. The TERT was a protein product by the hTERT gene in the locus 5p15.33 (NCBI Genome Annotation; NT023089) The NBP2 was a protein product by the ABCC3 (ATP-binding cassette, sub-family C) gene in the locus 17q22 (NCBI Genome Annotation; NT010783). 5. In the Pedant-Pro database analysis, the predictable protein structure of the OFC1 gene had at least one transmembrane region and one non-globular region.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.802-808
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• 2009

Recently many researches have been presented to improve the clustering performance of gene expression data by incorporating Gene Ontology into the process of clustering. In particular, Kustra et al. showed higher performance improvement by exploiting Biological Process Ontology compared to the typical expression-based clustering. This paper extends the work of Kustra et al. by performing extensive experiments on the way of incorporating GO structures. To this end, we used three ontological distance measures (Lin's, Resnik's, Jiang's) and three GO structures (BP, CC, MF) for the yeast expression data. From all test cases, We found that clustering performances were remarkably improved by incorporating GO; especially, Resnik's distance measure based on Biological Process Ontology was the best.

• Information and Communications Magazine
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• v.29 no.11
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• pp.48-54
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• 2012

정보통신 기술은 아날로그 산업에서 디지털 산업을 거쳐 현재는 스마트 산업으로 이어지는 수단으로 활용되어 왔다. 특히 산업 사회생활에서 문서로 직접 주고받던 환경에서 메일, 전자문서 교환 등으로 바뀌면서 편리성과 비용절감을 통해 산업 사회생활 발전에 기여하고 있다. 최근 빅데이터 기술은 대용량 정보를 분석하여 기상예측, 신약개발, 유전자 분석 등의 다양한 분야에 활용되고 있다. 그러나 대용량 정보 안에는 개인 식별을 할 수 있는 정보가 포함되어 있어, 빅데이터 기술을 바로 적용하기에는 개인정보보호법이 정하는 개인정보보호 이용에 관한 법률에 대한 준비가 미흡한 실정이다. 예를 들어 공공기관의 데이터를 활용하여 날씨 예측, 재난 방재 서비스 등을 통해 국민의 삶을 제고함과 동시에 경제적으로 많은 이익을 가져올 수 있다. 그러나 개인정보를 타인이 악의적으로 이용할 수 있어 개인에게 경제적, 정신적 피해를 줄 수 있다. 또한 개인정보의 노출은 과거와 달리 삭제되거나 잊혀지지 않고 영구적으로 재사용이 가능하기 때문에 이를 사전에 막을 수 있는 방법이 필요하다. 이에 본고는 빅데이터 등장에 따른 시장구조 변화 및 경제적 파급효과를 분석하고, 법리적 분석을 바탕으로 빅데이터 기술이 올바르게 시장에 정착할 수 있은 법(규제)방안을 제시하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.187-188
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• 2016

열대열 말라리아(Plasmodium falciparum, P. falciparum, P. f) 신속진단키트의 경우, P. falciparum에 특이적인 단백질로써 Histidine Rich Protein 2 (PfHRP2)가 사용되고 있다. 그러나 최근 연구에서 남아메리카와 중앙아메리카를 중심으로 pfhrp2/pfhrp3 유전자가 결여된 P. falciparum 열원충이 나타나는 것으로 보고된 바 있다. 본 연구에서는 생물정보학을 기반으로 PfHRP2 항원 단백질을 대체할 수 있는 새로운 P. falciparum 특이 항원 단백질을 선정하고자, PlasmoDB에서 5,777개의 P. falciparum 관련 단백질 리스트를 얻었다. 이후 NCBI BLAST를 통해 단백질 아미노산 서열을 분석하고 정상인에게 존재하지 않으며, 동시에 다른 말라리아 열원충(P. vivax, P. ovale, P. malariae, P. knowlesi)에도 존재하지 않는 P. falciparum 특이 아미노산 서열을 가진 단백질 15개를 추출하였다. IEDB analysis를 이용하여 에피토프, 수용성, 베타-턴, 접근성, 유연성, 면역원성을 분석하여 높은 평균값을 갖는 상위 3개 단백질을 선별하였다. KEGG pathway와 EMBL-EBI를 통해 선별된 3개 단백질의 혈액내 검출 가능성 및 아미노산 서열의 보존성을 분석하여 최종적으로 Glutamate-Rich Protein (GLURP)을 선정하였다. AIDA를 통해 단백질 아미노산 서열을 이용한 3차 구조 예측으로 GLURP의 구조 및 항체와의 결합을 도식화하였다. 최종적으로 선정한 GLURP는 pfhrp2/pfhrp3 유전자 결여 P. falciparum까지 특이적으로 진단이 가능하여 차세대 P. falciparum 특이 신속진단키트 개발에 도움이 될 수 있을 것으로 기대한다.

• Korean Journal of Ichthyology
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• v.23 no.1
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• pp.10-20
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• 2011

Genetic determinant for metallothionein (MT), a cysteine-rich protein playing essential roles in metal detoxification and homeostasis, was characterized in the Korean bitterling (Acheilognathus signifer, Cyprinidae), an endemic fish species. The full-length A. signifer MT (AsMT) cDNA (551 bp) is composed of a single open-reading frame (ORF) to encode a polypeptide of 60 amino acids containing 20 cysteine residues whose positions are conserved in most cypriniform MTs. At the genomic level, the AsMT (2,593 bp spanning the 5'-flanking region to the 3'-untranslated region) represented a conserved tripartite (three exons interrupted by two introns) structure with AT-rich introns. The upstream regulatory region (-1,914 bp from the ATG initiation codon) of AsMT displayed various sites and motifs for transcription factors involved in the metal-mediated regulation and stress/immune responses. The AsMT transcript was ubiquitously detected in various organs with variable expression levels, where the ovary and intestine showed the highest expression, while the heart and skeletal muscle represented the lowest level. During an exposure to copper (immersion in $0.5\;{\mu}M$ Cu for 48 h), the levels of AsMT transcripts were significantly elevated in the liver (more than 3.5-fold), moderately in the gill, kidney, and spleen (ranging from 1.5- to 2.5-fold), and barely in the brain and intestine. Results of this study could form a useful basis to explore the metal-related stress physiology of this endangered fish species.