Selective Phenome Growth Adapted NK Model: A Novel Landscape to Represent Aptamer Ligand Binding
Joint Authors
Kinghorn, Andrew Brian
Tanner, Julian Alexander
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-24
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Aptamers are single-stranded oligonucleotides selected by evolutionary approaches from massive libraries with significant potential for specific molecular recognition in diagnostics and therapeutics.
A complete empirical characterisation of an aptamer selection experiment is not feasible due to the vast complexity of aptamer selection.
Simulation of aptamer selection has been used to characterise and optimise the selection process; however, the absence of a good model for aptamer-target binding limits this field of study.
Here, we generate theoretical fitness landscapes which appear to more accurately represent aptamer-target binding.
The method used to generate these landscapes, selective phenome growth, is a new approach in which phenotypic contributors are added to a genotype/phenotype interaction map sequentially in such a way so as to increase the fitness of a selected fit sequence.
In this way, a landscape is built around the selected fittest sequences.
Comparison to empirical aptamer microarray data shows that our theoretical fitness landscapes more accurately represent aptamer ligand binding than other theoretical models.
These improved fitness landscapes have potential for the computational analysis and optimisation of other complex systems.
American Psychological Association (APA)
Kinghorn, Andrew Brian& Tanner, Julian Alexander. 2017. Selective Phenome Growth Adapted NK Model: A Novel Landscape to Represent Aptamer Ligand Binding. Complexity،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1143301
Modern Language Association (MLA)
Kinghorn, Andrew Brian& Tanner, Julian Alexander. Selective Phenome Growth Adapted NK Model: A Novel Landscape to Represent Aptamer Ligand Binding. Complexity No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1143301
American Medical Association (AMA)
Kinghorn, Andrew Brian& Tanner, Julian Alexander. Selective Phenome Growth Adapted NK Model: A Novel Landscape to Represent Aptamer Ligand Binding. Complexity. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1143301
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143301