• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.23-28
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• 2005

The high-dimensionality and insufficiency of gene expression profiles and proteomic profiles makes feature selection become a critical step in efficiently building accurate models for cancer problems based on such data sets. In this paper, we use a method, called Discrete Function Learning algorithm, to find discriminatory feature vectors based on information theory. The target feature vectors contain all or most information (in terms of entropy) of the class attribute. Two data sets are selected to validate our approach, one leukemia subtype gene expression data set and one ovarian cancer proteomic data set. The experimental results show that the our method generalizes well when applied to these insufficient and high-dimensional data sets. Furthermore, the obtained classifiers are highly understandable and accurate.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.754-759
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• 2007

In this paper, we proposed the Bi-Modal Sensor Fusion Algorithm which is the emotional recognition method that be able to classify 4 emotions (Happy, Sad, Angry, Surprise) by using facial image and speech signal together. We extract the feature vectors from speech signal using acoustic feature without language feature and classify emotional pattern using Neural-Network. We also make the feature selection of mouth, eyes and eyebrows from facial image. and extracted feature vectors that apply to Principal Component Analysis(PCA) remakes low dimension feature vector. So we proposed method to fused into result value of emotion recognition by using facial image and speech.

• BMB Reports
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• 제39권3호
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• pp.329-334
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• 2006

RNAi (RNA interference) has become a popular means of knocking down a specific gene in vivo. The most common approach involves the use of chemically synthesized short interfering RNAs (siRNAs), which are relatively easy and fast to use, but which are costly and have only transient effects. These limitations can be overcome by using short hairpin RNA (shRNA) expression vectors. However, current methods of generating shRNA expression vectors require either the synthesis of long (50-70 nt) costly oligonucleotides or multi-step processes. To overcome this drawback, we have developed a one-step short-oligonucleotides-based method with preparation costs of only 15% of those of the conventional methods used to obtain essentially the same DNA fragment encoding shRNA. Sequences containing 19 bases homologous to target genes were synthesized as 17- and 31-nt DNA oligonucleotides and used to construct shRNA expression vectors. Using these plasmids, we were able to effectively silence target genes. Because our method relies on the onestep ligation of short oligonucleotides, it is simple, less error-prone, and economical.

• 한국수학교육학회지시리즈A:수학교육
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• 제56권1호
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• pp.63-80
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• 2017

By analysing the examination papers from third grade high school students, we classified the errors occurred in the problem solving process of high school 'Geometry and Vectors' into several types. There are five main types - (A)Insufficient Content Knowledge, (B)Wrong Method, (C)Logical Invalidity, (D)Unskilled Expression and (E)Interference.. Type A and B lead to an incorrect answer, and type C and D cannot be distinguished by multiple-choice or closed answer questions. Some of these types are classified into subtypes - (B1)Incompletion, (B2)Omitted Condition, (B3)Incorrect Calculation, (C1)Non-reasoning, (C2)Insufficient Reasoning, (C3)Illogical Process, (D1)Arbitrary Symbol, (D2)Using a Character Without Explanation, (D3) Visual Dependence, (D4)Symbol Incorrectly Used, (D5)Ambiguous Expression. Based on the these types of errors, answers of each problem was analysed in detail, and proper ways to correct or prevent these errors were suggested case by case. When problems that were used in the periodical test were given again in descriptive forms, 67% of the students tried to answer, and 14% described flawlessly, despite that the percentage of correct answers were higher than 40% when given in multiple-choice form. 34% of the students who tried to answer have failed to have logical validity. 37% of the students who tried to answer didn't have enough skill to express. In lessons on curves of secondary degree, teachers should be aware of several issues. Students are easily confused between 'focus' and 'vertex', and between 'components of a vector' and 'coordinates of a point'. Students often use an undefined expression when mentioning a parallel translation. When using a character, students have to make sure to define it precisely, to prevent the students from making errors and to make them express in correct ways.

• 한국동물학회지
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• 제38권4호
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• pp.550-556
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• 1995

c-myc proto-oncogene은 여러 세포들의 분화와 형질전화에 뿐만 아니라 정상세포의 분열조절에도 관여한다고 알려져왔다. 특히 생쥐의 초기배아에서 c-myc mRNA가 발현되고 antisense c-myc oligomer의 미세주입에 의해 배발생이 억제된다는 연구결과는 c-myc이 초기배아의 발생 및 분열에 관여하는 것을 시사한다. 그러나 최근까지 초기배아에 존재하는 c-myc promoter의 기능적 활성화에 관한 연구는 미진하였다. 이를 위하여, c-myc promoter와 대장균의 lacZ 유전자를 결합시킨 두 종류의 vector(pcmyc-Gall, pcmyc-Ga12)를 만들어 수정란의 전핵에 미세주입한 후, 배 발생에 따른 c-myc promoter의 활성화를 lacZ 유전자의 산물인 $\beta$-galactosidase 에 의한 X-gal 염색으로 조사하였다. 미세주입된 초기 배아는 2세포기 배아를 포함하는 여러 발생단계에서 $\beta$-galactosidase 의 활성을 보였다. 이는 c-myc 유전자가 배아의 게놈유전자로부터 발현되며, 또한 궁극적으로 초기 배아의 발생과정에 중요한 역할을 하고 있음을 시사하고 있다.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2001년도 추계학술발표대회
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• pp.70-73
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• 2001

Isopentenyl diphosphate (IPP) is the common, five-carbon building block in the biosynthesis of all isoprenoids. IPP in Escherichia coli is synthesized through the non-mevalonate pathway. The first reaction of IPP biosynthesis in E. coli is the formation of 1-deoxy-D-xylulose-5-phosphate(DXP), catalyzed by DXP synthase and encoded by dxs. The second reaction in the pathway is the reduction of DXP to 2-C-methyl-D-erythritol-4-phosphate, catalyzed by DXP reductoismerase and encoded by dxr. To determine if one of more of the reactions in the non-mevalonate pathway controlled flux to IPP, dxs and dxr were placed on several expression vectors under the control of three different promoters and transformed into three E. coli strains ($DH5{\alpha}$, XL1-Blue, and JM101) that had been engineered to produce lycopene, a kind of isoprenoids. Lycopene production was improved significantly in strains transformed with the dex expression vectors. At arabinose concentrations between 0 and 1.33 mM, cells expressiong both dxs and from $P_{BAD}$ on a midium-copy plasmid produced 1.4 -2.0 times more lycopene than cells expressing dxs only. However, at higher arabinose concentrations lycopene production in cell expressing both dxs and dxr was lower than in cells expression dxs only. A comparison of the three E. coli strains trasfomed with the arabinose-inducible dxs on a medium-copy plasmid revealed that lycopene production was highest in XL1-Blue.

• BMB Reports
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• 제28권3호
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• pp.216-220
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• 1995

cDNA for human cholesteryl ester transfer protein (CETP), a potent atherogenic plasma protein that redistributes the neutral lipids among lipoproteins, was expressed in recombinant vaccinia virus-infected cells (CV-1). Two insertion vectors regulated by different promoters were constructed. The vectors were introduced into human thymidine kinase-negative ($TK^-$) 1438 cells infected with wild-type vaccinia virus (WR strain). Recombinant viruses were selected with 5-bromodeoxyuridine (BUdR) and X-gal and identified with DNA dot blot analysis (vSC11-CETP and vTM1-CETP). The CETP cDNA insert in the recombinant vaccinia virus genome was identified by Southern blot analysis. Transcription of CETP cDNA in CV-1 cells infected with recombinant vaccinia virus was monitored by Northern blot analysis using the CETP cDNA as a probe. Positive signals were detected at 1.8 kb in cells infected with vSC11-CETP and at 2.3 kb in cells infected with vTM1-CETP. The recombinant vaccinia virus-infected CV-1 cells were shown to produce functional CETP when the culture medium was subjected to the CETP assay.

• 한국멀티미디어학회논문지
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• 제12권8호
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• pp.1155-1163
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• 2009

본 논문에서는 가우시안 프로세스 모델을 이용한 벡터 그래픽 캐릭터의 자동 표정 생성 시스템을 제안한다. 제안한 방법은 Russell의 내적 정서 상태의 차원 모형을 근거로 재정의된 캐릭터의 26가지 표정 데이터로 부터 주요 특징 벡터를 추출한다. 그리고 추출된 고차원의 특징 벡터에 대해 SGPLVM이라는 가우시안 프로세스 모델을 이용하여 저차원 특징 벡터를 찾고, 확률분포함수(PDF)를 학습한다. 확률분포함수의 모든 파라메타는 학습된 표정 데이터의 우도를 최대화함으로써 추정할 수 있으며, 이는 2차원 공간에서 사용자가 원하는 얼굴 표정을 실시간으로 선택하기 위해 사용된다. 시뮬레이션 결과 본 논문에서 제안한 표정 생성 프로그램은 얼굴 표정의 작은 데이터셋에도 잘 동작하며, 사용자는 표정과 정서간의 관련성에 관한 사전지식이 없이도 연속되는 다양한 캐릭터의 표정을 생성할 수 있음을 확인할 수 있었다.

• 한국지능시스템학회논문지
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• 제16권6호
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• pp.759-765
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• 2006

본 논문에서는 퍼지 소속 함수와 웨이브렛 기저를 이용한 효과적인 얼굴 표정 인식 LDA 융합모델을 제안하였다. 제안된 알고리즘은 최적의 영상을 얻기 위해 퍼지 웨이브렛 알고리즘을 수행하고, 표정 검출은 얼굴 특징 추출단계와 얼굴표절인식 단계로 구성된다. 본 논문에서 얼굴 표정이 담긴 영상을 PCA를 적용하여 고차원에서 저차원의 공간으로 변환 후, LDA 특성을 이용하여 클래스 별호 특징벡터를 분류한다. LDA 융합 모델은 얼굴 표정인식단계는 제안된 LDA융합모델의 특징 벡터에 NNPC를 적응함으로서 얼굴 표정을 인식한다. 제안된 알고리즘은 6가지 기본 감정(기쁨, 화남, 놀람, 공포, 슬픔, 혐오)으로 구성된 데이터베이스를 이용해 실험한 결과, 기존알고리즘에 비해 향상된 인식률과 특정 표정에 관계없이 고른 인식률을 보임을 확인하였다.

• Mycobiology
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• 제45권2호
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• pp.84-89
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• 2017

Fungi of the Metarhizium genus are a very versatile model for understanding pathogenicity in insects and their symbiotic relationship with plants. To establish a co-transformation system for the transformation of multiple M. robertsii genes using Agrobacterium tumefaciens, we evaluated whether the antibiotic nourseothricin has the same marker selection efficiency as phosphinothricin using separate vectors. Subsequently, in the two vectors containing the nourseothricin and phosphinothricin resistance cassettes were inserted eGFP and mCherry expression cassettes, respectively. These new vectors were then introduced independently into A. tumefaciens and used to transform M. robertsii either in independent events or in one single co-transformation event using an equimolar mixture of A. tumefaciens cultures. The number of transformants obtained by co-transformation was similar to that obtained by the individual transformation events. This method provides an additional strategy for the simultaneous insertion of multiple genes into M. robertsii.