![](/images/graphics-bg.png)
Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm
Joint Authors
Zhang, Yu-Hang
Wang, ShaoPeng
Lu, Jing
Cui, Weiren
Hu, Jerry
Cai, Yu-Dong
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-03
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes.
Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention.
However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment.
Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds.
This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection.
Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds.
As a result, some important features were obtained.
To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions.
Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions.
The program is available upon the request.
American Psychological Association (APA)
Wang, ShaoPeng& Zhang, Yu-Hang& Lu, Jing& Cui, Weiren& Hu, Jerry& Cai, Yu-Dong. 2016. Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm. BioMed Research International،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099034
Modern Language Association (MLA)
Wang, ShaoPeng…[et al.]. Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm. BioMed Research International No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1099034
American Medical Association (AMA)
Wang, ShaoPeng& Zhang, Yu-Hang& Lu, Jing& Cui, Weiren& Hu, Jerry& Cai, Yu-Dong. Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099034
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099034