• Molecules and Cells
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• 제24권3호
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• pp.307-315
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• 2007

Gene regulation is a fundamental process in biological systems, where transcription factors (TFs) play crucial roles. Inferring transcriptional interactions between TFs and their target genes has utmost importance for understanding the complex regulatory mechanisms in cellular systems. On one hand, with the rapid progress of various high-throughput experiment techniques, more and more biological data become available, which makes it possible to quantitatively study gene regulation in a systematic manner. On the other hand, transcription regulation is a complex biological process mediated by many events such as post-translational modifications, degradation, and competitive binding of multiple TFs. In this review, with a particular emphasis on computational methods, we report the recent advances of the research topics related to transcriptional regulatory networks, including how to infer transcriptional interactions, reveal combinatorial regulation mechanisms, and reconstruct TF activity profiles.

• Biomolecules & Therapeutics
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• 제28권6호
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• pp.503-511
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• 2020

Autophagy is a major catabolic process that maintains cell metabolism by degrading damaged organelles and other dysfunctional proteins via the lysosome. Abnormal regulation of this process has been known to be involved in the progression of pathophysiological diseases, such as cancer and neurodegenerative disorders. Although the mechanisms for the regulation of autophagic pathways are relatively well known, the precise regulation of this pathway in the treatment of cancer remains largely unknown. It is still complicated whether the regulation of autophagy is beneficial in improving cancer. Many studies have demonstrated that autophagy plays a dual role in cancer by suppressing the growth of tumors or the progression of cancer development, which seems to be dependent on unknown characteristics of various cancer types. This review summarizes the key targets involved in autophagy and malignant transformation. In addition, the opposing tumor-suppressive and oncogenic roles of autophagy in cancer, as well as potential clinical therapeutics utilizing either regulators of autophagy or combinatorial therapeutics with anti-cancer drugs have been discussed.

• Molecules and Cells
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• 제45권7호
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• pp.444-453
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• 2022

Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.

• International Journal of Contents
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• 제8권4호
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• pp.74-77
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• 2012

Radiation has been an effective tool for treating cancer for a long time. Radiation therapy induces DNA damage within cancer cells and destroys their ability to reproduce. Radiation therapy is often combined with other treatments, like surgery and chemotherapy. Here, we describe the effects of radiation and histone deacetylase inhibitor, Trichostain A, on cell cycle regulation in hepatoma cells. The combinatorial treatment of radiation and Trichostain A induced cell cycle arrest and thereby increasing the hepatoma cell death. Furthermore, the regulatory effects of radiation and Trichostatin A on cell cycle applied in cell type specifically. These results suggest that the treatment of radiation and Trichostatin A may play a central role in hepatoma cell death and might be a good remedy to improve the efficiency of radiation therapy.

• Genomics & Informatics
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• 제5권4호
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• pp.143-151
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• 2007

To understand the mechanism of transcriptional regulation, it is essential to detect promoters and regulatory elements. Various kinds of methods have been introduced to improve the prediction accuracy of regulatory elements. Since there are few experimentally validated regulatory elements, previous studies have used criteria based solely on the level of scores over background sequences. However, selecting the detection criteria for different prediction methods is not feasible. Here, we studied the calibration of thresholds to improve regulatory element prediction. We predicted a regulatory element using MATCH, which is a powerful tool for transcription factor binding site (TFBS) detection. To increase the prediction accuracy, we used a regulatory potential (RP) score measuring the similarity of patterns in alignments to those in known regulatory regions. Next, we calibrated the thresholds to find relevant scores, increasing the true positives while decreasing possible false positives. By applying various thresholds, we compared predicted regulatory elements with validated regulatory elements from the Open Regulatory Annotation (ORegAnno) database. The predicted regulators by the selected threshold were validated through enrichment analysis of muscle-specific gene sets from the Tissue-Specific Transcripts and Genes (T-STAG) database. We found 14 known muscle-specific regulators with a less than a 5% false discovery rate (FDR) in a single TFBS analysis, as well as known transcription factor combinations in our combinatorial TFBS analysis.

• Journal of Mechanical Science and Technology
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• 제15권3호
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• pp.300-308
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• 2001

Tracking of moving objects within video streams is a complex and time-consuming process. Large number of moving objects increases the time for computation of tracking the moving objects. Because of large computations, there are real-time processing problems in tracking of moving objects. Also, the change of environment causes errors in estimation of tracking information. In this paper, we present a new method for tracking of moving objects using optical flow motion analysis. Optical flow represents an important family of visual information processing techniques in computer vision. Segmenting an optical flow field into coherent motion groups and estimating each underlying motion are very challenging tasks when the optical flow field is projected from a scene of several moving objects independently. The problem is further complicated if the optical flow data are noisy and partially incorrect. Optical flow estimation based on regulation method is an iterative method, which is very sensitive to the noisy data. So we used the Combinatorial Hough Transform (CHT) and Voting Accumulation for finding the optimal constraint lines. To decrease the operation time, we used logical operations. Optical flow vectors of moving objects are extracted, and the moving information of objects is computed from the extracted optical flow vectors. The simulation results on the noisy test images show that the proposed method finds better flow vectors and more correctly estimates the moving information of objects in the real time video streams.

• IMMUNE NETWORK
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• 제14권6호
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• pp.265-276
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• 2014

The interactions between B7 molecules and CD28-family receptors are crucial in the regulation of adaptive cellular immunity. In cancer, the aberrant expression of co-inhibitory B7 molecules has been attributed to reduced anti-tumor immunity and cancer immune evasion, prompting the development of cancer therapeutics that can restore T cell function. Murine tumor models have provided significant support for the targeting of multiple immune checkpoints involving CTLA-4, PD-1, ICOS, B7-H3 and B7-H4 during tumor growth, and clinical studies investigating the therapeutic effects of CTLA-4 and PD-1 blockade have shown exceptionally promising results in patients with advanced melanoma and other cancers. The expression pattern of co-inhibitory B7 ligands in the tumor microenvironment has also been largely correlated with poor patient prognosis, and recent evidence suggests that the presence of several B7 molecules may predict the responsiveness of immunotherapies that rely on pre-existing tumor-associated immune responses. While monotherapies blocking T cell co-inhibition have beneficial effects in reducing tumor burden, combinatorial immunotherapy targeting multiple immune checkpoints involved in various stages of the anti-tumor response has led to the most substantial impact on tumor reduction. In this review, we will examine the contributions of B7- and CD28-family members in the context of cancer development, and discuss the implications of current human findings in cancer immunotherapy.

• Journal of Microbiology and Biotechnology
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• 제22권7호
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• pp.1029-1033
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• 2012

A number of evidence have been accumulated that the regulation of reversible tyrosine phosphorylation, which can be regulated by the combinatorial activity of protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs), plays crucial roles in various biological processes including differentiation. There are a total of 107 PTP genes in the human genome, collectively referred to as the "PTPome." In this study, we performed PTP profiling analysis of the HIB-1B cell line, a brown preadipocyte cell line, during brown adipogenesis. Through RT-PCR and real-time PCR, several PTPs showing differential expression pattern during brown adipogenesis were identified. In the case of PTP-RE, it was shown to decrease significantly until 4 days after brown adipogenic differentiation, followed by a dramatic increase at 6 days. The overexpression of PTP-RE led to decreased brown adipogenic differentiation via reducing the tyrosine phosphorylation of the insulin receptor, indicating that PTP-RE functions as a negative regulator at the early stage of brown adipogenesis.

• Biomolecules & Therapeutics
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• 제18권1호
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• pp.39-47
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• 2010

Brain-derived neurotrophic factor (BDNF) is a neurotrophic factor involved in neuronal differentiation, plasticity, survival and regeneration. BDNF draws massive attention mainly due to the potential as a therapeutic target in neurological diseases such as depression and Alzheimer's disease. In a primary screening for the natural compounds enhancing BDNF release from cultured rat primary cortical neuron, we found that compounds such as baicalein, tanshinone IIa, cinnamic acid, epiberberine, genistein and wogonin among many others increased BDNF release. All the compounds at $0.1{\mu}M$ of concentration barely showed stimulatory effect on BDNF induction, however, their combination (mixture 1; baicalein, tanshinone IIa and cinnamic acid, mixture 2; epiberberine, genistein and wogonin) showed synergistic increase in BDNF release as well as mRNA and protein expression. The level of BDNF expression was comparable to the maximum BDNF stimulation attainable by a positive control oroxylin A ($20{\mu}M$) without cell toxicity as determined by MTT analysis. Both mixtures synergistically increased the phosphorylation of extracellular signal-regulated kinase (ERK) as well as cAMP response element binding protein (CREB), an immediate and essential regulator of BDNF expression. Similar to these results, mixture of these compounds synergistically inhibited the up-regulation of inducible nitric oxide synthase (iNOS) induced by lipopolysaccharide treatments in rat primary astrocytes. These results suggest that the combinatorial treatment of natural compounds in lower concentration might be a useful strategy to obtain sufficient BDNF stimulation in neurological disease condition such as depression, while minimizing potential side effects and toxicity of higher concentration of a single compound.

• 지능정보연구
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• 제21권4호
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• pp.1-16
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• 2015

교통사고의 원인을 규명하고 미래의 사고를 방지하기 위한 노력의 일환으로 데이터 마이닝 기법을 이용한 교통 데이터 분석의 연구가 이루어지고 있다. 하지만 기존의 교통 데이터를 이용한 마이닝 연구들은 학습된 결과를 사람이 이해하기 어려워 분석에 많은 노력이 필요하다는 문제가 있었다. 본 논문에서는 많은 속성들로 표현된 교통사고 데이터로부터 유용한 패턴을 발견하기 위해 규칙 학습 기반의 데이터 마이닝 기법인 연관규칙 학습기법과 서브그룹 발견기법을 적용하였다. 연관규칙 학습기법은 비지도 학습 기법의 하나로 데이터 내에서 동시에 많이 등장하는 아이템(item)들을 찾아 규칙의 형태로 가공해 주며, 서브그룹 발견기법은 사용자가 지정한 대상 속성이 결론부에 나타나는 규칙을 학습하는 지도학습 기반 기법으로 일반성과 흥미도가 높은 규칙을 학습한다. 규칙 학습 시 사용자의 의도를 반영하기 위해서는 하나 이상의 관심 속성들을 조합한 합성 속성을 만들어 규칙을 학습할 수 있다. 규칙이 도출되고 나면 후처리 과정을 통해 중복된 규칙을 제거하고 유사한 규칙을 일반화하여 규칙들을 더 단순하고 이해하기 쉬운 형태로 가공한다. 교통사고 데이터를 대상으로 두 기법을 적용한 결과 대상 속성을 지정하지 않고 연관규칙 학습기법을 적용하는 경우 사용자가 쉽게 알기 어려운 속성 사이의 숨겨진 관계를 발견할 수 있었으며, 대상 속성을 지정하여 연관규칙 학습기법과 서브그룹 발견기법을 적용하는 경우 파라미터 조정에 많은 노력을 기울여야 하는 연관규칙 학습기법에 비해 서브그룹 발견기법이 흥미로운 규칙들을 더 쉽게 찾을 수 있음을 확인하였다.