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Junhyeok Jeon,Hyun Uk Kim 한국미생물학회 2020 The journal of microbiology Vol.58 No.3
Computational analysis of biological data is becoming increasingly important, especially in this era of big data. Computational analysis of biological data allows efficiently deriving biological insights for given data, and sometimes even counterintuitive ones that may challenge the existing knowledge. Among experimental researchers without any prior exposure to computer programming, computational analysis of biological data has often been considered to be a task reserved for computational biologists. However, thanks to the increasing availability of user-friendly computational resources, experimental researchers can now easily access computational resources, including a scientific computing environment and packages necessary for data analysis. In this regard, we here describe the process of accessing Jupyter Notebook, the most popular Python coding environment, to conduct computational biology. Python is currently a mainstream programming language for biology and biotechnology. In particular, Anaconda and Google Colaboratory are introduced as two representative options to easily launch Jupyter Notebook. Finally, a Python package COBRApy is demonstrated as an example to simulate 1) specific growth rate of Escherichia coli as well as compounds consumed or generated under a minimal medium with glucose as a sole carbon source, and 2) theoretical production yield of succinic acid, an industrially important chemical, using E. coli. This protocol should serve as a guide for further extended computational analyses of biological data for experimental researchers without computational background.
『성경(星鏡)』에 기록된 항성: 『의상고성속편(儀象考成續編)』 성표와의 연관성을 고려한 동정
전준혁 ( Jeon Junhyeok ) 한국과학사학회 2017 한국과학사학회지 Vol.39 No.1
In the late Joseon period, an astronomical text titled Seonggyeong 星鏡 (Stars Reflected in the Mirror) was published by Nam Byeong-Gil 南秉 吉 (1820-1869). This study aims to critically review the identification of stars in Seonggyeong by previous scholars, and to re-identify them by considering its relationship with the star catalogue of Yixiang kaocheng xubian 儀象考成 續編. In doing so, new methods, including overlap analysis and pattern analysis, are applied. Of the 1,449 stars recorded in Seonggyeong, this paper identifies 1,413 stars (97.5 percent). The positional error of the identified stars is 5.33±0.34 arc-min. This study also confirms that the magnitudes of the recorded stars have correlations with those of modern times. It is determined that the positional errors of the stars grow larger as the magnitude of the stars become dimmer, or as the position of the stars come closer to the pole. Based on these analyses, this paper finally suggests that Seonggyeong was compiled through selecting the East Asian traditional stars recorded in the star catalogue of Yixiang kaocheng xubian, while at the same time completely correcting the precession.
제지슬러지소각재 및 킬레이트제 활용 간접탄산화 방법을 통한 이산화탄소 저장 및 탄산칼슘 생성
전준혁,김명진,Jeon, Junhyeok,Kim, Myoung-Jin 한국자원리싸이클링학회 2019 資源 리싸이클링 Vol.28 No.3
In this study, we conducted experiments to store $CO_2$ and produce $CaCO_3$ through indirect carbonation using paper sludge ash (PSA) and three chelating reagents (fumarate, IDA and EDTA). Fumarate and IDA used as solvents could facilitate the indirect carbonation reaction to store more $CO_2$ than water. When 0.1 M fumarate and IDA were used, $CO_2$ storage was 63 and $89kg-CO_2/ton-PSA$, respectively, and $CaCO_3$ yield was 144 and $202kg-CaCO_3/ton-PSA$. For the case of EDTA, however, the carbonation was hardly progressed. As either the concentration or Ca-ligand stabilization constant of each chelating reagent increased, the calcium extraction efficiency from PSA increased. In addition, the carbonation efficiency was influenced by the Ca-ligand stabilization constant. As the Ca-ligand stabilization constant increased, more calcium could be extracted from the PSA. With the constant larger than that of $CaCO_3$ ($10^{8.35}$), however, the carbonation reaction was not proceeded.