Model-based study of the Effectiveness of Reporting Lists of Small Feature Sets using RNA-Seq Data-Reference-Cited by-同舟云学术

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Model-based study of the Effectiveness of Reporting Lists of Small Feature Sets using RNA-Seq Data

Published:2016-10-02 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
language:
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Author:

Kim Eunji¹,Ivanov Ivan²,Hua Jianping¹,Chapkin Robert S.³,Dougherty Edward R.¹

Affiliation:

1. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX

2. Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX

3. Program in Integrative Nutrition & Complex Diseases, Texas A&M University, College Station, TX

Funder

National Institutes of Health

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2975167.2985636

Reference4 articles.

1. Superior feature-set ranking for small samples using bolstered error estimation

2. Characterization of the Effectiveness of Reporting Lists of Small Feature Sets Relative to the Accuracy of the Prior Biological Knowledge

3. Modeling the next generation sequencing sample processing pipeline for the purposes of classification

4. Performance of feature-selection methods in the classification of high-dimension data

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