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George C Runger

Showing results (1-10 of 10) with videos related to

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IEEE Transactions on Neural Networks and Learning Systems|July 11, 2018
GCRNN: Group-Constrained Convolutional Recurrent Neural NetworkSangdi Lin, George C Runger
Bioinformatics (Oxford, England)|October 18, 2019
Matched Forest: supervised learning for high-dimensional matched case-control studiesNooshin Shomal Zadeh, Sangdi Lin, George C Runger
IEEE Transactions on Neural Networks and Learning Systems|May 9, 2014
Tangent hyperplane kernel principal component analysis for denoisingJoon-Ku Im, Daniel W Apley, George C Runger
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 16, 2009
A novel feature selection methodology for automated inspection systemsHugo C Garcia, Jesus Rene Villalobos, Rong Pan, et al.
Bioinformatics (Oxford, England)|May 19, 2009
Integrative analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: a non-linear model to predict abundance of undetected proteinsWandaliz Torres-García, Weiwen Zhang, George C Runger, et al.
Molecular Biosystems|January 8, 2011
Integrative analysis of transcriptomic and proteomic data of Shewanella oneidensis: missing value imputation using temporal datasetsWandaliz Torres-García, Steven D Brown, Roger H Johnson, et al.
Molecular Biosystems|January 7, 2012
A statistical framework for multiparameter analysis at the single-cell levelWandaliz Torres-García, Shashanka Ashili, Laimonas Kelbauskas, et al.
BMC Genomics|November 29, 2018
A data science approach for the classification of low-grade and high-grade ovarian serous carcinomasSangdi Lin, Chen Wang, Shabnam Zarei, et al.
Plos One|June 29, 2018
Correction: Performance of next-generation sequencing on small tumor specimens and/or low tumor content samples using a commercially available platformScott M Morris, Janakiraman Subramanian, Esma S Gel, et al.
Plos One|April 28, 2018
Performance of next-generation sequencing on small tumor specimens and/or low tumor content samples using a commercially available platformScott M Morris, Janakiraman Subramanian, Esma S Gel, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Neural Networks and Learning Systems|July 11, 2018
GCRNN: Group-Constrained Convolutional Recurrent Neural NetworkSangdi Lin, George C Runger
Bioinformatics (Oxford, England)|October 18, 2019
Matched Forest: supervised learning for high-dimensional matched case-control studiesNooshin Shomal Zadeh, Sangdi Lin, George C Runger
IEEE Transactions on Neural Networks and Learning Systems|May 9, 2014
Tangent hyperplane kernel principal component analysis for denoisingJoon-Ku Im, Daniel W Apley, George C Runger
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 16, 2009
A novel feature selection methodology for automated inspection systemsHugo C Garcia, Jesus Rene Villalobos, Rong Pan, et al.
Bioinformatics (Oxford, England)|May 19, 2009
Integrative analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: a non-linear model to predict abundance of undetected proteinsWandaliz Torres-García, Weiwen Zhang, George C Runger, et al.
Molecular Biosystems|January 8, 2011
Integrative analysis of transcriptomic and proteomic data of Shewanella oneidensis: missing value imputation using temporal datasetsWandaliz Torres-García, Steven D Brown, Roger H Johnson, et al.
Molecular Biosystems|January 7, 2012
A statistical framework for multiparameter analysis at the single-cell levelWandaliz Torres-García, Shashanka Ashili, Laimonas Kelbauskas, et al.
BMC Genomics|November 29, 2018
A data science approach for the classification of low-grade and high-grade ovarian serous carcinomasSangdi Lin, Chen Wang, Shabnam Zarei, et al.
Plos One|June 29, 2018
Correction: Performance of next-generation sequencing on small tumor specimens and/or low tumor content samples using a commercially available platformScott M Morris, Janakiraman Subramanian, Esma S Gel, et al.
Plos One|April 28, 2018
Performance of next-generation sequencing on small tumor specimens and/or low tumor content samples using a commercially available platformScott M Morris, Janakiraman Subramanian, Esma S Gel, et al.
Pageof 1