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Renaissance Distribution for Statistically Failed Experiments
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 obtai...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651062/ https://www.ncbi.nlm.nih.gov/pubmed/31269680 http://dx.doi.org/10.3390/ijms20133250 |
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author | Popov, Roman Shankara, Girish Karadka von Bojničić-Kninski, Clemens Nesterov-Mueller, Alexander |
author_facet | Popov, Roman Shankara, Girish Karadka von Bojničić-Kninski, Clemens Nesterov-Mueller, Alexander |
author_sort | Popov, Roman |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6651062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66510622019-08-07 Renaissance Distribution for Statistically Failed Experiments Popov, Roman Shankara, Girish Karadka von Bojničić-Kninski, Clemens Nesterov-Mueller, Alexander Int J Mol Sci Article 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. MDPI 2019-07-02 /pmc/articles/PMC6651062/ /pubmed/31269680 http://dx.doi.org/10.3390/ijms20133250 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Popov, Roman Shankara, Girish Karadka von Bojničić-Kninski, Clemens Nesterov-Mueller, Alexander Renaissance Distribution for Statistically Failed Experiments |
title | Renaissance Distribution for Statistically Failed Experiments |
title_full | Renaissance Distribution for Statistically Failed Experiments |
title_fullStr | Renaissance Distribution for Statistically Failed Experiments |
title_full_unstemmed | Renaissance Distribution for Statistically Failed Experiments |
title_short | Renaissance Distribution for Statistically Failed Experiments |
title_sort | renaissance distribution for statistically failed experiments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651062/ https://www.ncbi.nlm.nih.gov/pubmed/31269680 http://dx.doi.org/10.3390/ijms20133250 |
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