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Dan Tulpan

Showing results (11-20 of 39) with videos related to

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BMC Genomics|April 19, 2015
Enrichment of Triticum aestivum gene annotations using ortholog cliques and gene ontologies in other plantsDan Tulpan, Serge Leger, Alain Tchagang, et al.
Journal of Animal Science|February 4, 2025
Prediction of Pellet Durability Index in a commercial feed mill using multiple linear regression with variable selection and dimensionality reductionJihao You, Dan Tulpan, Cheryl Krziyzek, et al.
BMC Bioinformatics|March 18, 2017
Bioinformatics identification of new targets for improving low temperature stress tolerance in spring and winter wheatAlain B Tchagang, François Fauteux, Dan Tulpan, et al.
Metabolites|October 6, 2016
Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant MetabolitesMiroslava Cuperlovic-Culf, NandhaKishore Rajagopalan, Dan Tulpan, et al.
Biomed Research International|August 29, 2013
HyDEn: a hybrid steganocryptographic approach for data encryption using randomized error-correcting DNA codesDan Tulpan, Chaouki Regoui, Guillaume Durand, et al.
Frontiers in Plant Science|December 9, 2021
Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration MethodsMohsen Yoosefzadeh-Najafabadi, Sepideh Torabi, Dan Tulpan, et al.
BMC Bioinformatics|October 18, 2011
MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixturesDan Tulpan, Serge Léger, Luc Belliveau, et al.
Journal of Animal Science|December 24, 2025
ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Construction of supervised machine learning regression pipelines for livestock data modeling: A case studyDan Tulpan, Luis O Tedeschi, Hector Menendez, et al.
Plants (Basel, Switzerland)|July 29, 2023
Application of SVR-Mediated GWAS for Identification of Durable Genetic Regions Associated with Soybean Seed Quality TraitsMohsen Yoosefzadeh-Najafabadi, Sepideh Torabi, Dan Tulpan, et al.
Frontiers in Plant Science|January 29, 2021
Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in SoybeanMohsen Yoosefzadeh-Najafabadi, Hugh J Earl, Dan Tulpan, et al.
Pageof 4

Showing results (11-20 of 39) with videos related to

Sort By:
Pageof 4
BMC Genomics|April 19, 2015
Enrichment of Triticum aestivum gene annotations using ortholog cliques and gene ontologies in other plantsDan Tulpan, Serge Leger, Alain Tchagang, et al.
Journal of Animal Science|February 4, 2025
Prediction of Pellet Durability Index in a commercial feed mill using multiple linear regression with variable selection and dimensionality reductionJihao You, Dan Tulpan, Cheryl Krziyzek, et al.
BMC Bioinformatics|March 18, 2017
Bioinformatics identification of new targets for improving low temperature stress tolerance in spring and winter wheatAlain B Tchagang, François Fauteux, Dan Tulpan, et al.
Metabolites|October 6, 2016
Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant MetabolitesMiroslava Cuperlovic-Culf, NandhaKishore Rajagopalan, Dan Tulpan, et al.
Biomed Research International|August 29, 2013
HyDEn: a hybrid steganocryptographic approach for data encryption using randomized error-correcting DNA codesDan Tulpan, Chaouki Regoui, Guillaume Durand, et al.
Frontiers in Plant Science|December 9, 2021
Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration MethodsMohsen Yoosefzadeh-Najafabadi, Sepideh Torabi, Dan Tulpan, et al.
BMC Bioinformatics|October 18, 2011
MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixturesDan Tulpan, Serge Léger, Luc Belliveau, et al.
Journal of Animal Science|December 24, 2025
ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Construction of supervised machine learning regression pipelines for livestock data modeling: A case studyDan Tulpan, Luis O Tedeschi, Hector Menendez, et al.
Plants (Basel, Switzerland)|July 29, 2023
Application of SVR-Mediated GWAS for Identification of Durable Genetic Regions Associated with Soybean Seed Quality TraitsMohsen Yoosefzadeh-Najafabadi, Sepideh Torabi, Dan Tulpan, et al.
Frontiers in Plant Science|January 29, 2021
Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in SoybeanMohsen Yoosefzadeh-Najafabadi, Hugh J Earl, Dan Tulpan, et al.
Pageof 4