Popov R, Shankara GK, von Bojničić-Kninski C, Nesterov-Mueller A. Renaissance Distribution for Statistically Failed Experiments.
Int J Mol Sci 2019;
20:ijms20133250. [PMID:
31269680 PMCID:
PMC6651062 DOI:
10.3390/ijms20133250]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 06/26/2019] [Accepted: 06/30/2019] [Indexed: 11/25/2022] Open
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.
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