• Food Science of Animal Resources
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• v.43 no.3
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• pp.540-551
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• 2023

Milk protein concentrate (MPC) is widely used to enhance the stability and texture of fermented dairy products. However, most research has focused on yogurt products, and the effects of MPC on sour cream characteristics remain unknown. Therefore, we investigated the effects of different MPC levels (0%, 1%, 2%, and 3% w/w) on the rheological, physicochemical, microbiological, and aroma characteristics of sour creams in this study. We found that MPC supplementation stimulated the growth of lactic acid bacteria (LAB) in sour creams, resulting in higher acidity than that in the control sample due to the lactic acid produced by LAB. Three aroma compounds, acetaldehyde, diacetyl, and acetoin, were detected in all sour cream samples. All sour creams showed shear-thinning behavior (n=0.41-0.50), and the addition of MPC led to an increase in the rheological parameters (η_a,50, K, G', and G"). In particular, sour cream with 3% MPC showed the best elastic property owing to the interaction between denatured whey protein and caseins. In addition, these protein interactions resulted in the formation of a gel network, which enhanced the water-holding capacity and improved the whey separation. These findings revealed that MPC can be used as a supplementary protein to improve the rheological and physicochemical characteristics of sour cream.

• Biotechnology and Bioprocess Engineering:BBE
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• v.6 no.5
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• pp.326-331
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• 2001

With the aim of developing of pH-sensitive controlled drug release system, a poly(Llysine) (PLL) based cationic semi-interpenetrating polymer network (semi-IPN) has been synthesized. This cationic hydrogel was designed to swell at lower pH and de-swell at higher pH and therefore be applicable for achieving regulated drug release at a specific pH range. In addition to the pH sensitivity, this hydrogel was anticipated to interact with an ionic drug, providing another means to regulate the release rate of ionic drugs. This semi-IPN hydrogel was prepared using a free-radical polymerization method and by crosslinking of the polyethylene glycol (PEG)-methacrylate polymer through the PLL network. The two polymers were penetrated with each other via interpolymer complexation to yield the semi-IPN structures. The PLL hydrogel thus prepared showed dynamic swelling/de-swelling behavior in response to pH change, and such a behavior was influenced by both the concentrations of PLL and PEG-methacrylate. Drug release from this semi-IPN hydrogel was also investigated using a model protein drug, streptokinase. Streptokinase release was found to be dependent on its ionic interaction with the PLL backbones as well as on the swelling of the semi-IPN hydrogel. These results suggest that a PLL semi-IPN hydrogel could potentially be used as a drug delivery platform to modulate drug release by pH-sensitivity and ionic interaction.

• Genomics & Informatics
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• v.19 no.4
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• pp.42.1-42.17
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• 2021

Salivary gland carcinoma (SGC) is rare cancer, constituting 6% of neoplasms in the head and neck area. The most responsible genes and pathways involved in the pathology of this disorder have not been fully understood. We aimed to identify differentially expressed genes (DEGs), the most critical hub genes, transcription factors, signaling pathways, and biological processes (BPs) associated with the pathogenesis of primary SGC. The mRNA dataset GSE153283 in the Gene Expression Omnibus database was re-analyzed for determining DEGs in cancer tissue of patients with primary SGC compared to the adjacent normal tissue (adjusted p-value < 0.001; |Log2 fold change| > 1). A protein interaction map (PIM) was built, and the main modules within the network were identified and focused on the different pathways and BP analyses. The hub genes of PIM were discovered, and their associated gene regulatory network was built to determine the master regulators involved in the pathogenesis of primary SGC. A total of 137 genes were found to be differentially expressed in primary SGC. The most significant pathways and BPs that were deregulated in the primary disease condition were associated with the cell cycle and fibroblast proliferation procedures. TP53, EGF, FN1, NOTCH1, EZH2, COL1A1, SPP1, CDKN2A, WNT5A, PDGFRB, CCNB1, and H2AFX were demonstrated to be the most critical genes linked with the primary SGC. SPIB, FOXM1, and POLR2A significantly regulate all the hub genes. This study illustrated several hub genes and their master regulators that might be appropriate targets for the therapeutic aims of primary SGC.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.89-100
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• 2011

The CNV (Copy Number Variation) which is one of the genetic structural variations in human genome is closely related with the function of gene. In particular, the genome-wide association studies for genetic diseased persons have been researched. However, there have been few studies which infer the genetic function of CNV with normal human. In this paper, we propose the analysis method to reveal the functional relationship between common CNV and genes without considering their genomic loci. To achieve that, we propose the data integration method for heterogeneity biological data and novel measurement which can calculate the correlation between common CNV and genes. To verify the significance of proposed method, we has experimented several verification tests with GO database. The result showed that the novel measurement had enough significance compared with random test and the proposed method could systematically produce the candidates of genetic function which have strong correlation with common CNV.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.474-492
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• 2007

In the protein interaction network, there are many meaningful functional modules, each involving several protein interactions to perform discrete functions. Pathways and protein complexes are the examples of the functional modules. In this paper, we propose a new method for detecting the functional modules based on concept. A conceptual functional module, briefly concept module is introduced to match the modules taking them as its instances. It is defined by the corresponding rule composed of triples and operators between the triples. The triples represent conceptual relations reifying the protein interactions of a module, and the operators specify the structure of the module with the relations. Furthermore, users can define a composite concept module by the counterpart rule which, in turn, is defined in terms of the predefined rules. The concept module makes it possible to detect functional modules that are conceptually similar as well as structurally identical to users' queries. The rules are managed in the XML format so that they can be easily applied to other networks of different species. In this paper, we also provide a visualized environment for intuitionally describing complexly structured rules.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.263-266
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• 2005

We made a stepping stone for asthma study by analyzing an asthma-specific protein-protein interaction network. It follows the power-law degree distribution and its hub nodes and skeleton frame of the network agreed with the prior knowledge about asthma pathway. This study is providing a systematic approach to analyze the complex effect of genes or to represent the frame of their relations associated with specific disease.

• Bulletin of the Korean Chemical Society
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• v.29 no.5
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• pp.1013-1017
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• 2008

Syndecan-3 is a cell-surface heparan sulfate proteoglycan, which performs a variety of functions during cell adhension process. It is also a coreceptor for growth factor, mediating cell-cell and cell-matrix interaction. Syndecan-3 contains a cytoplasmic domain potentially associated with the cytoskeleton. Syndecan-3 is specifically expressed in neuron cell and has related to neuron cell differentiation and development of actin filament in cell migration. Syndecans each have a unique, central, and variable (V) region in their cytoplasmic domains. And that region of syndecan-3 may modulate the interactions of the conserved C1 regions of the cytoplasmic domains by tyrosine phosphorylation. Cytoplasmic domain of syndecan-3 has been synthesized for NMR structural studies. The solution structure of syndecan-3 cytoplasmic domain has been determined by two-dimensional NMR spectroscopy and simulated-annealing calculation. The cytoplasmic domain of the syndecan proteins has a tendency to form a dimmer conformation with a central cavity, however, that of syndecan-3 demonstrated a monomer conformation with a flexible region near C-terminus. The structural information might add knowledge about the structure-function relationships among syndecan proteins.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.1
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• pp.217-231
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• 2015

This study aims to infer the gene-protein 'brings_about' chains of pancreatic cancer which were referred to in the pancreatic cancer related researches by constructing the gene-protein interaction network of pancreatic cancer. The chains can help us uncover publicly unknown knowledge that would develop as empirical studies for investigating the cause of pancreatic cancer. In this study, we applied a novel approach that grafts text mining and the main path analysis into Swanson's ABC model for expanding intermediate concepts to multi-levels and extracting the most significant path. We carried out text mining analysis on the full texts of the pancreatic cancer research papers published during the last ten-year period and extracted the gene-protein entities and relations. The 'brings_about' network was established with bio relations represented by bio verbs. We also applied main path analysis to the network. We found the main direct 'brings_about' path of pancreatic cancer which includes 14 nodes and 13 arcs. 9 arcs were confirmed as the actual relations emerged on the related researches while the other 4 arcs were arisen in the network transformation process for main path analysis. We believe that our approach to combining text mining analysis with main path analysis can be a useful tool for inferring undiscovered knowledge in the situation where either a starting or an ending point is unknown.

• Genomics & Informatics
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• v.19 no.2
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• pp.14.1-14.6
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• 2021

Coronavirus disease 2019 (COVID-19) is an on-going pandemic disease infecting millions of people across the globe. Recent reports of reduction in antibody levels and the re-emergence of the disease in recovered patients necessitated the understanding of the pandemic at the core level. The cases of multiple organ failures emphasized the consideration of different organ systems while managing the disease. The present study employed RNA sequencing data to determine the disease associated differentially regulated genes and their related protein interactions in several organ systems. It signified the importance of early diagnosis and treatment of the disease. A map of protein interactions of multiple organ systems was built and uncovered CAV1 and CTNNB1 as the top degree nodes. A core interactions sub-network was analyzed to identify different modules of functional significance. AR, CTNNB1, CAV1, and PIK3R1 proteins were unfolded as bridging nodes interconnecting different modules for the information flow across several pathways. The present study also highlighted some of the druggable targets to analyze in drug re-purposing strategies against the COVID-19 pandemic. Therefore, the protein interactions map and the modular interactions of the differentially regulated genes in the multiple organ systems would incline the scientists and researchers to investigate in novel therapeutics for the COVID-19 pandemic expeditiously.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.7-9
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• 2006

단백질 상호작용 관계들은 고 성능 실험 기법을 이용한 생물학적 실험에 의해서 대규모로 추출되고, 동시에 이들을 구성하는 단백질 데이터 역시 공공 데이터베이스에 빈번하게 갱신되고 있다. 이 갱신으로 인하여 인터넷을 통해 공개되는 공공 데이터베이스와 PPI(Protein-Protein interaction) 네트워크에 포함된 단백질 데이터가 서로 일치하지 않게 된다. 본 논문에서는 PPI 네트워크에 존재하는 단백질을 래퍼(Wrapper)를 이용하여 빈번하게 갱신되는 공공 데이터베이스의 단백질로 식별하고, 이 식별을 통해 PPI 네트워크에 존재하는 데이터들을 항상 최신 데이터로 동기화함으로써 데이터의 실시간성을 제공하고 데이터에 대한 신뢰도를 보장할 수 있도록 하였다.