• Journal of Life Science
• /
• v.26 no.9
• /
• pp.1097-1104
• /
• 2016

With the development of next generation sequencing (NGS), large numbers of transcriptional molecules have been discovered. Most transcripts are non -coding RNAs (ncRNAs). Among them, long non-coding RNAs (lncRNAs) with more than 200 nucleotides represent functional RNA molecule that will not be translated into protein. In plants, lncRNAs are transcribed by RNA polymerase II (Pol II) or Pol III, Pol VI and Pol V. After transcription of these lncRNAs, more RNA processing mechanisms such as splicing and polyadenylation occurs. The expression of plant lncRNAs is very low and is tissue specific. However, these lncRNAs are strongly induced by specific external stimuli. Because different external stimuli including environmental stresses induce a large number of plant lncRNAs, these lncRNAs have been gradually considered as new regulatory factors of various biological and development processes such as epigenetic repression, chromatin modification, target mimicry, photomorphogenesis, protein relocalization, environmental stress response, pathogen infection in plants. Moreover, some lncRNAs act as precursor of short RNAs. Although a large number of lncRNAs have been predicted and identified in plants, our current understanding of the biological function of these lncRNAs is still limited and their detailed regulatory mechanisms should be elucidated continuously. Here, we reviewed the biogenesis and regulation mechanisms of lncRNAs and summarized the molecular functions unraveled in plants.

• Journal of Life Science
• /
• v.34 no.5
• /
• pp.339-355
• /
• 2024

The pulmonary system is a highly complex system that can only be understood by integrating its functional and structural aspects. Hence, in vivo animal models are generally used for pathological studies of pulmonary diseases and the evaluation of inhalation toxicity. However, to reduce the number of animals used in experimentation and with the consideration of animal welfare, alternative methods have been extensively developed. Notably, the Organization for Economic Co-operation and Development (OECD) and the United States Environmental Protection Agency (USEPA) have agreed to prohibit animal testing after 2030. Therefore, the latest advances in biotechnology are revolutionizing the approach to developing in vitro inhalation models. For example, lung organ-on-a-chip (OoC) and organoid models have been intensively studied alongside advancements in three-dimensional (3D) bioprinting and microfluidic systems. These modeling systems can more precisely imitate the complex biological environment compared to traditional in vivo animal experiments. This review paper addresses multiple aspects of the recent in vitro modeling systems of lung OoC and organoids. It includes discussions on the use of endothelial cells, epithelial cells, and fibroblasts composed of lung alveoli generated from pluripotent stem cells or cancer cells. Moreover, it covers lung air-liquid interface (ALI) systems, transwell membrane materials, and in silico models using artificial intelligence (AI) for the establishment and evaluation of in vitro pulmonary systems.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.471-471
• /
• 2022

도시화로 인한 하천 건천화가 심각해짐에 따라 생태계 종 다양성 감소와 서식처 파괴 등 다양한 생태학적 문제가 발생한다. 건강한 하천 생태계를 유지하기 위해서는 유량 감소로 인한 수생태계 건강성 회복을 위해서는 어류 종에 따른 적합한 생태 유량을 산정해야 한다. 특히 발전방류로 인한 유량 변화는 하류에 서식하는 어류에 직접적인 영향을 미치므로 댐 방류량에 의한 서식처 면적 변화에 대한 연구가 필요하다. 이에 본 연구에서는 1) 낙동강 상류 구담교 유역을 대상으로 안동댐과 임하댐 유입량을 활용한 BBM (Building Block Methodology)을 구축하고, 2) 대상 하천의 River2D 모형을 구축하여, 3) 대표·대리 어종에 대한 자연유황과 BBM에 따른 가중가용면적(Weighted Usable Area, WUA)을 산정하였다. 2006년 ~ 2020년 자료를 기반으로, 시나리오1은 실측 유량을 활용하였으며, 시나리오2는 전체기간, 홍수년, 갈수년 그리고 평수년으로 구분하여 댐 유입량을 기반으로 산정한 BBM을 활용하였다. 시나리오 분석 결과, 가중가용면적이 감소하는 일부 기간도 존재하였으나, 전반적으로 BBM을 반영한 시나리오 2에서 서식처 면적이 증가하는 것으로 나타났다. 대표 어종 피라미의 경우 최대 약 18% 가중가용면적이 감소하는 기간이 존재하였으나, 최대 79%의 서식처 향상 효과가 나타났다. 대리어종 모래무지의 경우 마찬가지로 최대 약 18%의 서식처 감소 효과가 나타나는 기간이 존재하였으나, 최대 78%의 서식처 향상 효과가 나타나는 것으로 나타났다. 따라서 자연유황을 모방하여 댐 방류 패턴을 변경하는 것이 하류에 서식하는 어류의 서식처 개선에 더 효과적인 것으로 판단된다. 다만 서식처에 영향을 주는 물리적 요인(댐 방류량 등) 외에도 생물·화학적 요인이 존재하므로, 향후 다양한 요인을 고려한 연구를 통해 효과적인 서식처 개선 방안을 모색할 수 있을 것으로 기대된다.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.35 no.8
• /
• pp.847-853
• /
• 2011

Filiform hairs that respond to movements of the surrounding medium are the mechanoreceptors commonly found in arthropods and vertebrates. The hairs function as a sensory system for perceiving information produced by prey, predators, or conspecifics. A mathematical model is proposed, and the parametric analyses for the response of artificial filiform hair are conducted to design and predict the performance of a microfabricated device. The results for the Cytop hair, one of the most popular polymer optical fibers (POFs), show that the fundamental mode has a dominant effect on the hair behavior in an oscillating medium flow. The dynamic behavior of sensory hair is also dependent on the physical dimensions such as length and diameter. It is found that the artificial hair with a high elastic modulus does not show a resonance in the biologically important frequency range.

• The Korean Journal of Pesticide Science
• /
• v.6 no.4
• /
• pp.231-243
• /
• 2002

Starting with linear free energy relationships (LFER), drug design to mimic of the activated complexes at transition state, and hydrolysis mechanisms to control the potency and residual properties of pesticides were introduced and summarized for the necessity. In order to understand the searching or development of new agrochemicals by two dimensional quantitative structure-activity relationship (2D QSAR) methodology, a series of the various descriptors, steric constants, electronic constants including quantum pharmacological parameters and hydrophobic constants were classified and discussed for results of the several studied cases. In addition, the processes of development of new agrochemicals by QSAR techniques were introduced simply.

• Journal of Korea Water Resources Association
• /
• v.31 no.1
• /
• pp.59-69
• /
• 1998

A regression model with basin physiographic characteristics as independent variables was calibrated for regional flood frequency analysis. In case that high correlations existing among the independent variables the ridge regression has been known to have capability of overcoming the problems of multicollinearity. To optimize the ridge regression model the cost function including regularization parameter must be minimized. In this research the genetic algorithm was applied on this optimization problem. The genetic algorithm is a stochastic search method that mimic the metaphor of natural biological heredity. Using this method the regression model could have optimized and stable weights of variables.

• Smart Media Journal
• /
• v.9 no.3
• /
• pp.31-40
• /
• 2020

Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

• Journal of Life Science
• /
• v.23 no.3
• /
• pp.341-346
• /
• 2013

The disappearance of seaweed flora in some rocky areas, which is known as algal whitening, barren ground, coralline flats, or deforested areas, is associated with some species of coralline algae. To determine the biological characteristics of a representative species of crustose coralline alga, the 18S rDNA gene was sequenced to identify the genus Lithophyllum. According to its morphological and distributional characteristics, it was deduced to be L. yessoense. Viability was measured using triphenyl tetrazolium chloride and showed high viability from December to February. Culture conditions of $16^{\circ}C$, a 16 hr light, 8 hr dark cycle, and 30 ${\mu}E/m^2/s$ light intensity were optimal for maintaining the viability of the alga for up to five days. Included in the fatty acids was 9.7% ${\omega}$-3 eicosapentaenoic acid. An electron microscopy scan of the surface structure revealed round craters about 3.6 ${\mu}m$ in diameter, which were covered with rough, irregular, and angular polygon-shaped structures about 1.0 to 3.7 ${\mu}m$ in size. Based on the composition and structure found in our study, biomimetic coralline alga might become an environmentally friendly antifouling material against the attachment of soft foulants.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.8
• /
• pp.299-308
• /
• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• Journal of Sensor Science and Technology
• /
• v.21 no.1
• /
• pp.59-67
• /
• 2012

It was reported that the latest sensor technology allow an 65536 conductive polymer sensor array to be made with broad but overlapping selectivity to different families of chemicals emulating the characteristics found in biological olfaction. However, the supernumerary redundancy always accompanies great error and risk as well as an inordinate amount of computation time and local minima in signal processing, e.g. neural networks. In this paper, we propose a new method to reduce the number of sensor for analysis by reducing redundancy between sensors and by removing unstable sensors using the cosine similarity method and to decide on representative sensor using FCM(Fuzzy C-Means) algorithm. The representative sensors can be just used in analyzing. And, we introduce DWT(Discrete Wavelet Transform) for data compression in the time domain as preprocessing. Throughout experimental trials, we have done a comparative analysis between gas sensor data with and without reduced redundancy. The possibility and superiority of the proposed methods are confirmed through experiments.