Structure-Activity Relationships in Chromatography: Retention Prediction of Oligonucleotides with Support Vector Regression

Secondary structures of biopolymers have a significant influence on their molecular interactions with surfaces. With the aid of machine learning through support vector regression, the retention of oligonucleotides was modeled in ion‐pair reversed‐phase chromatography with high prediction accuracy (s...

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Veröffentlicht in:Angewandte Chemie International Edition Jg. 45; H. 42; S. 7009 - 7012
Hauptverfasser: Kohlbacher, Oliver, Quinten, Sascha, Sturm, Marc, Mayr, Bettina M., Huber, Christian G.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Weinheim WILEY-VCH Verlag 27.10.2006
WILEY‐VCH Verlag
Schlagworte:
bioinformatics
Chromatography
liquid chromatography
Models, Chemical
oligonucleotides
Oligonucleotides - chemistry
Regression Analysis
secondary structures
Structure-Activity Relationship
structure-activity relationships
Temperature
Thermodynamics
ISSN:1433-7851, 1521-3773
Online-Zugang:Volltext
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Zusammenfassung:Secondary structures of biopolymers have a significant influence on their molecular interactions with surfaces. With the aid of machine learning through support vector regression, the retention of oligonucleotides was modeled in ion‐pair reversed‐phase chromatography with high prediction accuracy (see diagram).
Bibliographie:We thank LC Packings, Amsterdam, for the provision of the capillary HPLC system.
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ArticleID:ANIE200602561
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1433-7851
1521-3773
DOI:10.1002/anie.200602561