Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Kyle A. McQuisten; Andrew S. Peek

doi:10.1371/journal.pone.0007522

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Open Access

Peer-reviewed

Research Article

Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Kyle A. McQuisten,

Affiliation Department of Bioinformatics, Integrated DNA Technologies, Inc., Coralville, Iowa, United States of America
⨯
Andrew S. Peek

* E-mail: andrew.peek@roche.com

Current address: Department of Bioinformatics, Roche Molecular Systems, Inc., Pleasanton, California, United States of America

Affiliation Department of Bioinformatics, Integrated DNA Technologies, Inc., Coralville, Iowa, United States of America
⨯

Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Kyle A. McQuisten,
Andrew S. Peek

Published: October 22, 2009
https://doi.org/10.1371/journal.pone.0007522

About the Authors

Kyle A. McQuisten

Affiliation Department of Bioinformatics, Integrated DNA Technologies, Inc., Coralville, Iowa, United States of America

Andrew S. Peek

* E-mail: andrew.peek@roche.com

Current address: Department of Bioinformatics, Roche Molecular Systems, Inc., Pleasanton, California, United States of America

Affiliation Department of Bioinformatics, Integrated DNA Technologies, Inc., Coralville, Iowa, United States of America

Competing Interests

KAM and ASP were employed at Integrated DNA Technologies, Inc. (IDT), a supplier of synthetic nucleic acids. IDT funded, in part, the authors in their analysis, interpretation and preparation of the results.

Author Contributions

Conceived and designed the experiments: ASP. Performed the experiments: ASP. Analyzed the data: ASP. Contributed reagents/materials/analysis tools: KAM. Wrote the paper: KAM ASP.

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Small interfering RNA
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Machine learning
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Support vector machines
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Forecasting
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Artificial neural networks
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Analysis of variance
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Statistical data
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Linear regression analysis
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