An Efficient Approach for Prediction of Nuclear Receptor and Their Subfamilies Based on Fuzzy k-Nearest Neighbor with Maximum Relevance Minimum Redundancy-Reference-Cited by-同舟云学术

An Efficient Approach for Prediction of Nuclear Receptor and Their Subfamilies Based on Fuzzy k-Nearest Neighbor with Maximum Relevance Minimum Redundancy

Published:2016-12-22 Issue:1 Volume:88 Page:129-136
ISSN:0369-8203
Container-title:Proceedings of the National Academy of Sciences, India Section A: Physical Sciences
language:en
Short-container-title:Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci.

Author:

Tiwari Arvind Kumar,Srivastava Rajeev

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy

Link

http://link.springer.com/article/10.1007/s40010-016-0325-6/fulltext.html

Reference35 articles.

1. Robinson Rechavi M, Garcia HE, Laudet V (2003) The nuclear receptor superfamily. J Cell Sci 116(4):585–586

2. Moore JT, Collins JL, Pearce KH (2006) The nuclear receptor superfamily and drug discovery. ChemMedChem 1(5):504–523

3. Bhasin M, Raghava GPS (2004) Classification of nuclear receptors based on amino acid composition and dipeptide composition. J Biol Chem 279(22):23262–23266

4. Cai J, Li Y (2005) Classification of nuclear receptor subfamilies with RBF kernel in support vector machine. In: Advances in neural networks–ISNN, pp. 680–685

5. Gao QB, Jin ZC, Ye XF, Wu C, He J (2009) Prediction of nuclear receptors with optimal pseudo amino acid composition. Anal Biochem 387(1):54–59

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Magnetorheological damper current estimation based on k-nearest neighbor algorithm;Journal of Intelligent Material Systems and Structures;2022-06-08

2. Fuzzy k-NN Based Classifiers for Time Series with Soft Labels;Information Processing and Management of Uncertainty in Knowledge-Based Systems;2020

3. Quality Management for Big 3D Data Analytics: A Case Study of Protein Data Bank;Proceedings of the 4th International Conference on Internet of Things, Big Data and Security;2019