• Journal of Microbiology and Biotechnology
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• v.17 no.5
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• pp.728-732
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• 2007

In the present article, a novel fusion expression vector for Escherichia coli was developed based on the pTORG plasmid, a derivative of pET32a. This vector, named pT7MT(GenBank Accession No DQ504436), carries a T7 promoter and it drives the downstream gene encoding Metallothionein 2A(MT2A). There are in-framed multiple cloning sites(MCS) downstream of the MT2A gene. A target gene can be cloned into the MCS and fused to the C-terminal of the MT2A gene in a compatible open reading frame(ORF) to achieve fusion expression. The metal-binding capability of MT2A allows the purification of fusion proteins by metal chelating affinity chromatography, known as $Ni^{2+}$-affinity chromatography. Using this expression vector, we successfully got the stable and high-yield expression of MT2A-GST and MT2A-Troponin I fusion proteins. These two proteins were easily purified from the supernatant of cell lysates by one-step $Ni^{2+}$-affinity chromatography. The final yields of MT2A-GST and MT2A-Troponin I were 30mg/l and 28mg/l in LB culture, respectively. Taken together, our data suggest that pT7MT can be applied as a useful expression vector for stable and high-yield production of fusion proteins.

• Journal of Microbiology and Biotechnology
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• v.24 no.4
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• pp.431-439
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• 2014

We report the construction of two Bacillus subtilis expression vectors, pBNS1/pBNS2. Both vectors are based on the strong promoter P43 and the ampicillin resistance gene expression cassette. Additionally, a fragment with the Shine-Dalgarno sequence and a multiple cloning site (BamHI, SalI, SacI, XhoI, PstI, SphI) were inserted. The coding region for the amyQ (encoding an amylase) signal peptide was fused to the promoter P43 of pBNS1 to construct the secreted expression vector pBNS2. The applicability of vectors was tested by first generating the expression vectors pBNS1-GFP/pBNS2-GFP and then detecting for green fluorescent protein gene expression. Next, the mannanase gene from B. pumilus Nsic-2 was fused to vector pBNS2 and we measured the mannanase activity in the supernatant. The mannanase total enzyme activity was 8.65 U/ml, which was 6 times higher than that of the parent strain. Our work provides a feasible way to achieve an effective transformation system for gene expression in B. subtilis and is the first report to achieve B. pumilus mannanase secretory expression in B. subtilis.

• Journal of Aquaculture
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• v.13 no.1
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• pp.29-37
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• 2000

In previously study we isolated several fish matrix attachment regions (MARs) capable of replicating the plasmid by itself. In this study we construct a fish expression vector pBaEGFP(+) containing mud loach ${\beta}$-actin promoter EGFP as reporter gene and SV40 signal. To analyze the effects of the fish expression vector respectively. The fish ARS containing constructs pBaEGFP(+)-ARSs were transfected cells with pBaEGFP(+)-ARS101 and pBaEGFP(+)-ARS223 reduced 10 days to 25 days and then was constant to 30 days after transfection while that of the control vector without ARS element was basal level. The intensity of both constructs showed about 30fold of the intensity compared with the control vector on 30days after transfection individually .E. coli back-transformation analysis shows that pBaEGFP(+)-ARS223 and pBaEGFP(+)-ARS905 maintain in episomal state at least 30 days after transfection. The result indicates that both may be able to replicate the vector in BF-2 cell. Therefore the matrix-attached ARSs enhancing expression of the reporter gene might be useful as a component o the expression vector for transgenic studies.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1465-1473
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• 2006

In this paper, we present an approach for facial expression recognition using Active Shape Models(ASM) and a state-based model in image sequences. Given an image frame, we use ASM to obtain the shape parameter vector of the model while we locate facial feature points. Then, we can obtain the shape parameter vector set for all the frames of an image sequence. This vector set is converted into a state vector which is one of the three states by the state-based model. In the classification step, we use the k-NN with the proposed similarity measure that is motivated on the observation that the variation-regions of an expression sequence are different from those of other expression sequences. In the experiment with the public database KCFD, we demonstrate that the proposed measure slightly outperforms the binary measure in which the recognition performance of the k-NN with the proposed measure and the existing binary measure show 89.1% and 86.2% respectively when k is 1.

• Journal of Microbiology and Biotechnology
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• v.25 no.7
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• pp.988-998
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• 2015

The filamentous fungus Aspergillus oryzae is a well-known expression host used to express homologous and heterologous proteins in a number of industrial applications. To facilitate higher yields of proteins of interest, we constructed the pAsOP vector to express heterologous proteins in A. oryzae. pAsOP carries a selectable marker, pyrG, derived from Aspergillus nidulans, and a strong promoter and a terminator of the amyB gene derived from A. oryzae. pAsOP transformed A. oryzae efficiently via the PEG-CaCl₂-mediated transformation method. As proof of concept, green fluorescent protein (GFP) was successfully expressed in A. oryzae transformed by pAsOP-GFP. Additionally, we identified a novel fungal α-amylase (PcAmy) gene from Penicillium sp. and cloned the gene into the vector. After transformation by pAsOPPcAmy, the α-amylase PcAmy from Penicillium sp. was successfully expressed in a heterologous host system for the first time. The α-amylase activity in the A. oryzae transformant was increased by 62.3% compared with the untransformed A. oryzae control. The PcAmy protein produced in the system had an optimum pH of 5.0 and optimum temperature of 30^oC. As a cold-adapted enzyme, PcAmy shows potential value in industrial applications because of its high catalytic activity at low temperature. Furthermore, the expression vector reported in this study provides promising utility for further scientific research and biotechnological applications.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.14-20
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• 2019

Currently, microarray gene expression data take advantage of the sufficient classification of cancers, which addresses the problems relating to cancer causes and treatment regimens. However, the sample size of gene expression data is often restricted, because the price of microarray technology on studies in humans is high. We propose enhancing the gene expression classification of support vector machines with generative adversarial networks (GAN-SVMs). A GAN that generates new data from original training datasets was implemented. The GAN was used in conjunction with nonlinear SVMs that efficiently classify gene expression data. Numerical test results on 20 low-sample-size and very high-dimensional microarray gene expression datasets from the Kent Ridge Biomedical and Array Expression repositories indicate that the model is more accurate than state-of-the-art classifying models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1547-1553
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• 2008

This paper presents a method that generates various facial expressions of vector graphic character by using the simplified principle component vector. First, we analyze principle components to the nine facial expression(astonished, delighted, etc.) redefined based on Russell's internal emotion state. From this, we find principle component vector having the biggest effect on the character's facial feature and expression and generate the facial expression by using that. Also we create natural intermediate characters and expressions by interpolating weighting values to character's feature and expression. We can save memory space considerably, and create intermediate expressions with a small computation. Hence the performance of character generation system can be considerably improved in web, mobile service and game that real time control is required.

• The KIPS Transactions:PartA
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• v.11A no.2
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• pp.189-194
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• 2004

This paper describes method to distribute much high-dimensional facial expression motion data to 2 dimensional space, and method to create facial expression animation by select expressions that want by realtime as animator navigates this space. In this paper composed expression space using about 2400 facial expression frames. The creation of facial space is ended by decision of shortest distance between any two expressions. The expression space as manifold space expresses approximately distance between two points as following. After define expression state vector that express state of each expression using distance matrix which represent distance between any markers, if two expression adjoin, regard this as approximate about shortest distance between two expressions. So, if adjacency distance is decided between adjacency expressions, connect these adjacency distances and yield shortest distance between any two expression states, use Floyd algorithm for this. To materialize expression space that is high-dimensional space, project on 2 dimensions using Sammon's Mapping. Facial animation create by realtime with animators navigating 2 dimensional space using user interface.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1155-1163
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• 2009

This paper proposes an automatic facial expression generation system of vector graphic character using gaussian process model. Proposed method extracts the main feature vectors from twenty-six facial data of character redefined based on Russell's internal emotion state. Also by using new gaussian process model, SGPLVM, we find low-dimensional feature data from extracted high-dimensional feature vectors, and learn probability distribution function (PDF). All parameters of PDF are estimated by maximization the likelihood of learned expression data, and these are used to select wanted facial expressions on two-dimensional space in real time. As a result of simulation, we confirm that proposed facial expression generation tool is working in the small facial expression datasets and can generate various facial expressions without prior knowledge about relation between facial expression and emotion.

• Journal of Microbiology and Biotechnology
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• v.24 no.2
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• pp.152-159
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• 2014

The regulation of protein tyrosine phosphorylation is mediated by protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs) and is essential for cellular homeostasis. Co-expression of PTKs with PTPs in Pichia pastoris was used to facilitate the expression of active PTKs by neutralizing their apparent toxicity to cells. In this study, the gene encoding phosphatase PTP1B with or without a blue fluorescent protein or peroxisomal targeting signal 1 was cloned into the expression vector pAG32 to produce four vectors. These vectors were subsequently transformed into P. pastoris GS115. The tyrosine kinases EGFR-2 and $PDGFR{\beta}$ were expressed from vector pPIC3.5K and were fused with a His-tag and green fluorescent protein at the N-terminus. The two plasmids were transformed into P. pastoris with or without PTP1B, resulting in 10 strains. The EGFR-2 and $PDGFR{\beta}$ fusion proteins were purified by $Ni^{2+}$ affinity chromatography. In the recombinant P. pastoris, the PTKs co-expressed with PTP1B exhibited higher kinase catalytic activity than did those expressing the PTKs alone. The highest activities were achieved by targeting the PTKs and PTP1B into peroxisomes. Therefore, the EGFR-2 and $PDGFR{\beta}$ fusion proteins expressed in P. pastoris may be attractive drug screening targets for anticancer therapeutics.