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统计失败实验的再分布。

Renaissance Distribution for Statistically Failed Experiments.

机构信息

Institute of Microstructure Technology, Karlsruhe Institute of Technology (KIT), 76344 Eggenstein-Leopoldshafen, Germany.

出版信息

Int J Mol Sci. 2019 Jul 2;20(13):3250. doi: 10.3390/ijms20133250.

Abstract

Much of the experimental data, especially in life sciences, is considered to be useless if it demonstrates a large standard deviation from the mean value. The Renaissance distribution, as presented in this study, allows one to extract true values from such statistical data with large noise. To obtain proof of the Renaissance distribution, high-throughput synthesis of deep substitutions for a target amino acid sequence was performed, and the known epitope was identified in assay with human serum antibodies. In addition, the Renaissance distribution was shown to approach the epitope affinity maturation by the deep alanine substitution. The Renaissance distribution may have an impact in the development of novel specific drugs.

摘要

如果实验数据显示出与平均值有较大的标准偏差,那么这些数据通常被认为是无用的,尤其是在生命科学领域。本研究中提出的复兴分布允许从具有较大噪声的此类统计数据中提取真实值。为了获得复兴分布的证明,对目标氨基酸序列进行了高通量的深度取代合成,并在与人血清抗体的测定中鉴定了已知的表位。此外,通过深度丙氨酸取代,证明复兴分布接近表位亲和力成熟。复兴分布可能会对新型特异性药物的开发产生影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cd8/6651062/f0e222a14177/ijms-20-03250-g001.jpg

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