• Molecules and Cells
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• 제27권6호
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• pp.629-634
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• 2009

G protein-coupled receptors (GPCRs) are part of multi-protein networks called 'receptosomes'. These GPCR interacting proteins (GIPs) in the receptosomes control the targeting, trafficking and signaling of GPCRs. PDZ domain proteins constitute the largest protein family among the GIPs, and the predominant function of the PDZ domain proteins is to assemble signaling pathway components into close proximity by recognition of the last four C-terminal amino acids of GPCRs. We present here a machine learning based approach for the identification of GPCR-binding PDZ domain proteins. In order to characterize the network of interactions between amino acid residues that contribute to the stability of the PDZ domain-ligand complex and to encode the complex into a feature vector, amino acid contact matrices and physicochemical distance matrix were constructed and adopted. This novel machine learning based method displayed high performance for the identification of PDZ domain-ligand interactions and allowed the identification of novel GPCR-PDZ domain protein interactions.

• Biomolecules & Therapeutics
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• 제14권2호
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• pp.75-82
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• 2006

Synaptic plasticity, which is a long lasting change in synaptic efficacy, underlies many neural processes like learning and memory. It has long been acknowledged that new protein synthesis is essential for both the expression of synaptic plasticity and memory formation and storage. Most of the research interests in this field have focused on the events regulating transcriptional activation of gene expression from the cell body and nucleus. Considering extremely differentiated structural feature of a neuron in CNS, a neuron should meet a formidable task to overcome spatial and temporal restraints to deliver newly synthesized proteins to specific activated synapses among thousands of others, which are sometimes several millimeters away from the cell body. Recent advances in synaptic neurobiology has found that almost all the machinery required for the new protein translation are localized inside or at least in the vicinity of postsynaptic compartments. These findings led to the hypothesis that dormant mRNAs are translationally activated locally at the activated synapse, which may enable rapid and delicate control of new protein synthesis at activated synapses. In this review, we will describe the mechanism of local translational control at activated synapses focusing on the role of cytoplasmic polyadenylation of dormant mRNAs.

• 한국축산식품학회지
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• 제44권2호
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• pp.284-298
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• 2024

Restructured meat (RM) products are gaining importance as an essential component of the meat industry due to consumers' interest in health benefits. RM products imply the binding or holding of meat, meat by-products, and vegetable proteins together to form a meat product with meat's sensory and textural properties. RM products provide consumers with diversified preferences like the intake of low salt, low fat, antioxidants, and high dietary fiber in meat products. From the point of environmental sustainability, RM may aid in combining underutilized products and low-valued meat by adequately utilizing them instead of dumping them as waste material. RM processing technique might also help develop diversified and new hybrid meat products. It is crucial to have more knowledge on the quality issues, selection of binding agents, their optimum proportion, and finally, the ideal processing techniques. It is observed in this study that the most crucial feature of RM could be its healthy products with reduced fat content, which aligns with the preferences of health-conscious consumers who seek low-fat, low-salt, high-fiber options with minimal synthetic additives. This review briefly overviews RM and the factors affecting the quality and shelf life. Moreover, it discusses the recent studies on binding agents in processing RM products. Nonetheless, the recent advancements in processing and market scenarios have been summarized to better understand future research needs. The purpose of this review was to bring light to the ways of sustainable and economical food production.

• Ocean and Polar Research
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• 제37권1호
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• pp.11-22
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• 2015

In-situ measurements are labor-intensive, time-consuming, and limited in their ability to observe currents with spatial variations in the surf zone. This paper proposes an optical image-based method of measurement of currents in the surf zone. This method measures nearshore currents by tracking in time wave breaking-induced foam patches from sequential images. Foam patches in images tend to be arrayed with irregular pixel intensity values, which are likely to remain consistent for a short period of time. This irregular intensity feature of a foam patch is characterized and represented as a keypoint using an image-based object recognition method, i.e., Scale Invariant Feature Transform (SIFT). The keypoints identified by the SIFT method are traced from time sequential images to produce instantaneous velocity fields. In order to remove erroneous velocities, the instantaneous velocity fields are filtered by binding them within upper and lower limits, and averaging the velocity data in time and space with a certain interval. The measurements that are obtained by this method are comparable to the results estimated by an existing image-based method of observing currents, named the Optical Current Meter (OCM).

• 한국컴퓨터정보학회논문지
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• 제16권10호
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• pp.219-228
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• 2011

본 연구는 다양한 언어 데이터 분석을 통해 최소주의에서의 확대투사원리에 대한 대안을 제시하는데 역점을 둔다. 확대투사원리는 두 가지 원리에서 도출되는데, 하나는 표준이론에서의 투사원리이고 다른 하나는 주어위치는 반드시 채워야 한다는 요건을 근거한다. 이 두 원리가 하나로 병합된 확대투사원리는 이후에 계속해서 그 개념이 변한다. 최소주의 출현 이전에는 격에 의존적이었으나, Chomsky(1995)의 최소주의 하에서는 범주자질 [D]의 특성으로 귀착된다. 그러나 본 연구에서는 위치 도치 구문, 허사 there 구문, 결속이론과 같은 구문에서의 다양한 언어 데이터를 분석하여 굴절어구의 지정어 위치는 최대로 투사된 어휘항목에 의해 반드시 채워져야 한다는 대안을 제시한다.

• Archives of Pharmacal Research
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• 제28권3호
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• pp.297-304
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• 2005

Naturally occurring flavonoids are known to modulate various inflammatory and immune processes. Based on structural property, in this study, molecular mechanism of flavonoids in modulating nitric oxide (NO) production and its signaling pathway were investigated using lipopolysaccharide (LPS)-activated RAW264.7 cells. Although flavonol-typed flavonoids (kaempferol and quercetin) more potently scavenged reactivity of nitric oxide ($\cdot$NO) as well as peroxynitrite (ONOO$\kappa$) than isoflavones (genistein and genistin), kaempferol, quercetin and genistein showed a little difference in inhibition of both inducible NO synthase expression and NO production, with IC$_{50}$ values of 13.9, 20.1 and 26.8 $\mu$M. However, there was a striking pattern related to structural feature in modulation of LPS-mediated signaling pathways. Thus, flavonols only inhibited transcription factor AP-1 activation, whereas isoflavones suppressed the DNA binding activation of NF-$\kappa$B and C/EBP$\beta$. Therefore, these data suggest that structural feature may be linked to decide drugs target molecule in LPS-mediated signaling pathways, rather than its potency.

• 정보보호학회논문지
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• 제28권6호
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• pp.1427-1437
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• 2018

최근 생체 인증 시스템이 확대됨에 따라, 생체 정보를 이용하여 공개키 기반구조(Bio-PKI)에 적용하는 연구들이 진행 중이다. Bio-PKI 시스템에서는 공개키를 생성하기 위해 생체 정보로부터 암호학적 키를 생성하는 과정이 필요하다. 암호학적 키 생성 방법 중 특성 정보를 숫자로 정량화하는 기법은 데이터 손실을 유발하고 이로 인해 키 추출 성능이 저하된다. 이 논문에서는 다중 분류 모델을 이용하여 생체 정보를 분류한 결과를 이용하여 키를 생성하는 방법을 제안한다. 제안하는 기법은 특성 정보의 손실이 없어 높은 키 추출 성능을 보였고, 여러 개의 분류 모델을 이용하기 때문에 충분한 길이의 키를 생성한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• BMB Reports
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• 제48권3호
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• pp.129-130
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• 2015

Autophagy is a tightly regulated lysosome-mediated catabolic process in eukaryotes that maintains cellular homeostasis. A distinguishable feature of autophagy is the formation of double- membrane structures, autophagosome, which envelopes the intracellular cargoes and finally degrades them by fusion with lysosomes. So far, many structures of Atg proteins working on the autophagosome formation have been reported, however those involved in autophagosome maturation, a fusion with lysosome, are relatively unknown. One of the molecules in autophagosome maturation, TECPR1, has been identified and recently, structural studies on both ATG5-TECPR1 and ATG5-ATG16L1 complexes revealed that TECPR1 and ATG16L1 share the same binding site on ATG5. These results, in combination with supporting biochemical and cellular biological data, provide an insight into a model for swapping ATG5 partners for autophagosome maturation.

• 대한핵의학회:학술대회논문집
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• 대한핵의학회 1999년도 제38차 추계학술대회
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• pp.38.2-38.2
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• 1999