• Title/Summary/Keyword: Biological pattern

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A Study on the Architectural Application of Biological Patterns (생물학적 패턴의 건축적 적용에 관한 연구)

  • Kim, Won Gaff
    • Korean Institute of Interior Design Journal
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    • v.21 no.2
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    • pp.35-45
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    • 2012
  • The development of digital media made the change of architectural paradigm from tectonic to the surface and pattern. This means the transition to the new kind of materiality and the resurrection of ornament. This study started as an aim to apply biological pattern to architectural design from the new perception of pattern. Architectural patterns in the early era appeared as ladders, steps, chains, trees, vortices. But since 21st century, we can find patterns in nature like atoms and molecular structures, fluid forms of dynamics and new geometrical pattern like fractal and first of all biological patterns like viruses and micro-organisms, Voronoi cells, DNA structure, rhizomes and various hybrids and permutations of these. Pattern became one of the most important elements and themes of contemporary architecture through the change of materiality and resurrection of ornament with the new perception of surface in architecture. One of the patterns that give new creative availability to the architectural design is biological pattern which is self-organized as an optimum form through interaction with environment. Biological patterns emerge mostly as self-replicating patterns through morphogenesis, certain geometrical patterns(in particular triangles, pentagons, hexagons and spirals). The architectural application methods of biological patterns are direct figural pattern of organism, circle pattern, polygon pattern, energy-material control pattern, differentiation pattern, parametric pattern, growth principle pattern, evolutionary ecologic pattern. These patterns can be utilized as practical architectural patterns through the use of computer programs as morphogenetic programs like L-system, MoSS program and genetic algorithm programs like Grasshoper, Generative Components with the help of computing technology like mapping and scripting.

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Gene Discovery Analysis from Mouse Embryonic Stem Cells Based on Time Course Microarray Data

  • Suh, Young Ju;Cho, Sun A;Shim, Jung Hee;Yook, Yeon Joo;Yoo, Kyung Hyun;Kim, Jung Hee;Park, Eun Young;Noh, Ji Yeun;Lee, Seong Ho;Yang, Moon Hee;Jeong, Hyo Seok;Park, Jong Hoon
    • Molecules and Cells
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    • v.26 no.4
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    • pp.338-343
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    • 2008
  • An embryonic stem cell is a powerful tool for investigation of early development in vitro. The study of embryonic stem cell mediated neuronal differentiation allows for improved understanding of the mechanisms involved in embryonic neuronal development. We investigated expression profile changes using time course cDNA microarray to identify clues for the signaling network of neuronal differentiation. For the short time course microarray data, pattern analysis based on the quadratic regression method is an effective approach for identification and classification of a variety of expressed genes that have biological relevance. We studied the expression patterns, at each of 5 stages, after neuronal induction at the mRNA level of embryonic stem cells using the quadratic regression method for pattern analysis. As a result, a total of 316 genes (3.1%) including 166 (1.7%) informative genes in 8 possible expression patterns were identified by pattern analysis. Among the selected genes associated with neurological system, all three genes showing linearly increasing pattern over time, and one gene showing decreasing pattern over time, were verified by RT-PCR. Therefore, an increase in gene expression over time, in a linear pattern, may be associated with embryonic development. The genes: Tcfap2c, Ttr, Wnt3a, Btg2 and Foxk1 detected by pattern analysis, and verified by RT-PCR simultaneously, may be candidate markers associated with the development of the nervous system. Our study shows that pattern analysis, using the quadratic regression method, is very useful for investigation of time course cDNA microarray data. The pattern analysis used in this study has biological significance for the study of embryonic stem cells.

Post-disturbance Recovery Pattern in the Soft Corals-Macroalgae Mixed Habitat in Jeju Island, Korea

  • Kim, Junsu;Hong, Seokwoo;Yang, Kwon Mo;Macias, Daniela;Kim, Jeong Ha
    • Journal of Marine Life Science
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    • v.6 no.2
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    • pp.117-123
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    • 2021
  • Post-disturbance recovery pattern of subtidal soft corals-macroalgae mixed community and the role of water depth were investigated. The experiment was conducted in a subtidal rock wall of Munseom, Jeju Island, Korea for 2.5 years. Artificial disturbance was done at established treatment plots at depths of 10, 15 and 20 m and were then compared with undisturbed control plots. After disturbance, recovery of soft corals was very slow, whereas macroalgae quickly occupied the plots and reached a similar level as the control in 6 months, and this pattern was consistent at all water depths. This unbalanced speed of recovery caused higher macroalgae establishment than soft corals in treatment compared to control plots, indicating a possible phase shift in the community structure. This study provides an important implication for the necessity of monitoring the influence of disturbance at a larger scale, from a conservation perspective of soft corals in Jeju coast.

An influence of mesohabitat structures (pool, riffle, and run) and land-use pattern on the index of biological integrity in the Geum River watershed

  • Calderon, Martha S.;An, Kwang-Guk
    • Journal of Ecology and Environment
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    • v.40 no.2
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    • pp.107-119
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    • 2016
  • Background: Previous studies on the biological integrity on habitat and landuse patterns demonstrated ecological stream health in the view of regional or macrohabitat scale, thus ignored the mesoscale habitat patterns of pool, riffle, and runs in the stream health analysis. The objective of this study was to analyze influences on the mesohabitat structures of pool, riffle, and run reaches on the fish guilds and biological integrity in Geum-River Watershed. Results: The mesohabitat structures of pool, riffle, and run reaches influenced the ecological stream health along with some close relations on the fish trophic and tolerance guilds. The mesoscale components altered chemical water quality such as nutrients (TN, TP) and BOD and these, then, determined the primary productions, based on the sestonic chlorophyll-a. The riffle-reach had good chemical conditions, but the pool-reach had nutrient enrichments. The riffle-reach had a predominance of insectivores, while the pool-reach has a predominance of omnivores. Also, the riffle-reach had high proportions of sensitive fish and insectivore fish, and the pool-reach had high proportions of tolerant species in the community composition. The intermediate fish species in tolerance and omnivorous fish species in the food linkage dominated the community in the watershed, and the sensitive and insectivorous fishes decreased rapidly with a degradation of the water quality. All the habitat patterns were largely determined by the land-use patterns in the watershed. Conclusions: Trophic guilds and tolerance guilds of fish were determined by land-use pattern and these determined the stream health, based on the Index of Biological Integrity. This study remarks the necessity to include additional variables to consider information provided by mesohabitats and land-use distributions within the selected stream stretch. Overall, our data suggest that land-use pattern and mesohabitat distribution are important factors to be considered for the trophic and tolerance fish compositions and chemical gradients as well as ecological stream health in the watershed.

Efficient Mining of Interesting Patterns in Large Biological Sequences

  • Rashid, Md. Mamunur;Karim, Md. Rezaul;Jeong, Byeong-Soo;Choi, Ho-Jin
    • Genomics & Informatics
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    • v.10 no.1
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    • pp.44-50
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    • 2012
  • Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.

QCanvas: An Advanced Tool for Data Clustering and Visualization of Genomics Data

  • Kim, Nayoung;Park, Herin;He, Ningning;Lee, Hyeon Young;Yoon, Sukjoon
    • Genomics & Informatics
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    • v.10 no.4
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    • pp.263-265
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    • 2012
  • We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.

The Influence of Light Reduction on the Growth of Microcystis aeruginosa and Variation of Environmental and Chemical Parameters in Large-scale Cultivation System

  • Yang, Taehui;Cho, Ja-young;Kang, Ha-jin;Lee, Chang Soo;Kim, Eui-jin
    • Korean Journal of Ecology and Environment
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    • v.53 no.4
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    • pp.336-343
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    • 2020
  • Large-scale cultivation of Microcystis aeruginosa in different light conditions was conducted for verifying the cell growth in a greenhouse system. Environmental and chemical parameters of the large-scale culture medium were measured for analyzing the interaction between M. aeruginosa and its symbiotic bacteria. During cultivation, a difference in cell growth pattern was observed between control (natural light) and light-limited groups (reduction of blue, green, and blue/green light, respectively). Comparing the control group, the light reduced groups showed slow and delayed cell growth through the cultivation period. Also, there is differences in the consuming pattern of total nitrogen and total phosphorus which indicated that the possibility of interaction between M. aeruginosa and symbiotic bacteria.

Understanding Cold and Hot Pattern Classification Based on Systems Biology (시스템 생리학에 기반한 한열 변증의 이해)

  • Lee, Soojin
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.30 no.6
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    • pp.376-384
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    • 2016
  • Systems biology is an emerging field aiming at a systems level understanding of living organisms and focusing on the characteristics of the whole network of them. The emergence of systems biology is partly because of the availability of huge amounts of data on organisms and the extensive support of computational technologies as the tools for understanding complex biological systems. The scientific understanding of Korean medicine has been obstructed because of the lack of proper methods examining the complex nature and the unique property of it. However, systems biology could give a chance understanding Korean medicine objectively and scientifically. Pattern classification is a unique tool of Korean medicine to diagnose and treat patients and systems biology would give a useful tool to interpret pattern classification. Various omics technologies has been used to explain the relations between pattern classification and biological factors and then many characteristics of pattern classification in various diseases have been discovered. Therefore, pattern classification could be a bridge to understand the features and differences of western medicine and Korean medicine and it could be a basis to develop pattern-based personalized medicine.

Quantum-based exact pattern matching algorithms for biological sequences

  • Soni, Kapil Kumar;Rasool, Akhtar
    • ETRI Journal
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    • v.43 no.3
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    • pp.483-510
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    • 2021
  • In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.