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Maura John

Showing results (1-10 of 7) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|September 8, 2023
Predicting Gene Regulatory Interactions Using Natural Genetic VariationMaura John, Dominik Grimm, Arthur Korte
Bioinformatics Advances|April 17, 2023
easyPheno: An easy-to-use and easy-to-extend Python framework for phenotype prediction using Bayesian optimizationFlorian Haselbeck, Maura John, Dominik G Grimm
Journal of Experimental Botany|July 2, 2024
The benefits of permutation-based genome-wide association studiesMaura John, Arthur Korte, Dominik G Grimm
Bioinformatics Advances|December 16, 2024
Population-aware permutation-based significance thresholds for genome-wide association studiesMaura John, Arthur Korte, Marco Todesco, et al.
Bioinformatics (Oxford, England)|September 20, 2022
Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributionsMaura John, Markus J Ankenbrand, Carolin Artmann, et al.
NAR Genomics and Bioinformatics|October 13, 2023
Superior protein thermophilicity prediction with protein language model embeddingsFlorian Haselbeck, Maura John, Yuqi Zhang, et al.
Frontiers in Plant Science|November 21, 2022
A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant speciesMaura John, Florian Haselbeck, Rupashree Dass, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Methods in Molecular Biology (Clifton, N.J.)|September 8, 2023
Predicting Gene Regulatory Interactions Using Natural Genetic VariationMaura John, Dominik Grimm, Arthur Korte
Bioinformatics Advances|April 17, 2023
easyPheno: An easy-to-use and easy-to-extend Python framework for phenotype prediction using Bayesian optimizationFlorian Haselbeck, Maura John, Dominik G Grimm
Journal of Experimental Botany|July 2, 2024
The benefits of permutation-based genome-wide association studiesMaura John, Arthur Korte, Dominik G Grimm
Bioinformatics Advances|December 16, 2024
Population-aware permutation-based significance thresholds for genome-wide association studiesMaura John, Arthur Korte, Marco Todesco, et al.
Bioinformatics (Oxford, England)|September 20, 2022
Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributionsMaura John, Markus J Ankenbrand, Carolin Artmann, et al.
NAR Genomics and Bioinformatics|October 13, 2023
Superior protein thermophilicity prediction with protein language model embeddingsFlorian Haselbeck, Maura John, Yuqi Zhang, et al.
Frontiers in Plant Science|November 21, 2022
A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant speciesMaura John, Florian Haselbeck, Rupashree Dass, et al.
Pageof 1