NDLI: Hybrid feature selection and peptide binding affinity prediction using an EDA based algorithm

Content Provider	IEEE Xplore Digital Library
Author	Shelke, K. Jayaraman, S. Ghosh, S. Valadi, J.
Copyright Year	2013
Description	Author affiliation: ECIP, C-DAC, Pune, India (Ghosh, S.) \|\| Shiv Nadar Univ., Pune, India (Valadi, J.) \|\| Center for Modeling & Simulation, Univ. of Pune, Pune, India (Shelke, K.; Jayaraman, S.)
Abstract	Protein function prediction is an important problem in functional genomics. Typically, protein sequences are represented by feature vectors. A major problem of protein datasets that increase the complexity of classification models is their large number of features. The process of drug discovery often involves the use of quantitative structure-activity relationship (QSAR) models to identify chemical structures that could have good inhibitory effects on specific targets and have low toxicity (non-specific activity). QSAR models are regression or classification models used in the chemical and biological sciences. Because of high dimensionality problems, a feature selection problem is imminent. In this study, we thus employ a hybrid Estimation of Distribution Algorithm (EDA) based filter-wrapper methodology to simultaneously extract informative feature subsets and build robust QSAR models. The performance of the algorithm was tested on the benchmark classification challenge datasets obtained from the CoePRa competition platform, developed in 2006. Our results clearly demonstrate the efficacy of a hybrid EDA filter-wrapper algorithm in comparison to the results reported earlier.
Starting Page	2384
Ending Page	2389
File Size	803016
Page Count	6
File Format	PDF
ISBN	9781479904532
e-ISBN	9781479904549
e-ISBN	9781479904525
DOI	10.1109/CEC.2013.6557854
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-20
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Vectors Feature extraction Probability distribution Classification algorithms Prediction algorithms Radio frequency Weighted Feature Ranking Feature Selection Protein Function Prediction Estimation of Distribution Algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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