详细信息
Exponentially modified Gaussian relevance to the distributions of translocation events in nanopore-based single molecule detection ( SCI-EXPANDED收录)
文献类型:期刊文献
英文题名:Exponentially modified Gaussian relevance to the distributions of translocation events in nanopore-based single molecule detection
作者:Gu, Zhen[1];Ying, Yi-Lun[2,3];Yan, Bing-Yong[4];Wang, Hui-Feng[4];He, Pin-Gang[1];Long, Yi-Tao[2,3]
机构:[1]E China Normal Univ, Dept Chem, Shanghai 200241, Peoples R China;[2]E China Univ Sci & Technol, Key Lab Adv Mat, Shanghai 200237, Peoples R China;[3]E China Univ Sci & Technol, Dept Chem, Shanghai 200237, Peoples R China;[4]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China
年份:2014
卷号:25
期号:7
起止页码:1029
外文期刊名:CHINESE CHEMICAL LETTERS
收录:;WOS:【SCI-EXPANDED(收录号:WOS:000340223400013)】;
基金:The authors acknowledge funding of the National Natural Science Foundation of China (No. 21327807). Y.-T. Long is grateful for funds from the National Science Fund for Distinguished Young Scholars of China (No. 21125522). Y.-L. Ying thanks the Sino-UK Higher Education Research Partnership for PhD Studies.
语种:英文
外文关键词:Nanopore; Single-molecule detection; Exponentially modified Gaussian
摘要:Nanopore technique plays an important role in single molecule detection, which illuminates the properties of an individual molecule by analyzing the blockage durations and currents. However, the traditional exponential function is lack of efficiency to describe the distributions of blockage durations in nanopore experiments. Herein, we introduced an exponentially modified Gaussian (EMG) function to fit the duration histograms of both simulated events and experimental events. In comparison with the traditional exponential function, our results demonstrated that the EMG provides a better fit while covers the entire range of the distributions. In particular, the fitted parameters of EMG could be directly used to discriminate the sequence length of the oligonucleotides at single molecule level. (C) 2014 Bing-Yong Yan, Hui-Feng Wang and Pin-Gang He. Published by Elsevier B.V.
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