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BioData mining

Showing results (281-290 of 671) with videos related to

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Biodata Mining|March 17, 2023
Genetics and precision health: the ecological fallacy and artificial intelligence solutionsScott M Williams, Jason H Moore
Biodata Mining|February 21, 2023
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classificationDavide Chicco, Giuseppe Jurman
Biodata Mining|March 4, 2026
Disease- and gene-specific deep learning for pathogenicity prediction of rare missense variants in cancer predisposition genesDa-Bin Lee, Hyun-Uk Kang, Kyu-Baek Hwang
Biodata Mining|December 10, 2025
Optimizing large language models for ontology-based annotation: a study on gene ontology in biomedical textsPratik Devkota, Somya D Mohanty, Prashanti Manda
Biodata Mining|August 11, 2020
Conservation machine learningMoshe Sipper, Jason H Moore
Biodata Mining|July 17, 2020
Merging microarray studies to identify a common gene expression signature to several structural heart diseasesOlga Fajarda, Sara Duarte-Pereira, Raquel M Silva, et al.
Biodata Mining|January 28, 2014
The multiscale backbone of the human phenotype network based on biological pathwaysChristian Darabos, Marquitta J White, Britney E Graham, et al.
Biodata Mining|June 13, 2014
Semi-supervised consensus clustering for gene expression data analysisYunli Wang, Youlian Pan
Biodata Mining|February 5, 2015
Integrative genomics and transcriptomics analysis of human embryonic and induced pluripotent stem cellsKirsti Laurila, Reija Autio, Lingjia Kong, et al.
Biodata Mining|July 1, 2014
An adaptive permutation approach for genome-wide association study: evaluation and recommendations for useRonglin Che, John R Jack, Alison A Motsinger-Reif, et al.
Pageof 68

Showing results (281-290 of 671) with videos related to

Sort By:
Pageof 68
Biodata Mining|March 17, 2023
Genetics and precision health: the ecological fallacy and artificial intelligence solutionsScott M Williams, Jason H Moore
Biodata Mining|February 21, 2023
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classificationDavide Chicco, Giuseppe Jurman
Biodata Mining|March 4, 2026
Disease- and gene-specific deep learning for pathogenicity prediction of rare missense variants in cancer predisposition genesDa-Bin Lee, Hyun-Uk Kang, Kyu-Baek Hwang
Biodata Mining|December 10, 2025
Optimizing large language models for ontology-based annotation: a study on gene ontology in biomedical textsPratik Devkota, Somya D Mohanty, Prashanti Manda
Biodata Mining|August 11, 2020
Conservation machine learningMoshe Sipper, Jason H Moore
Biodata Mining|July 17, 2020
Merging microarray studies to identify a common gene expression signature to several structural heart diseasesOlga Fajarda, Sara Duarte-Pereira, Raquel M Silva, et al.
Biodata Mining|January 28, 2014
The multiscale backbone of the human phenotype network based on biological pathwaysChristian Darabos, Marquitta J White, Britney E Graham, et al.
Biodata Mining|June 13, 2014
Semi-supervised consensus clustering for gene expression data analysisYunli Wang, Youlian Pan
Biodata Mining|February 5, 2015
Integrative genomics and transcriptomics analysis of human embryonic and induced pluripotent stem cellsKirsti Laurila, Reija Autio, Lingjia Kong, et al.
Biodata Mining|July 1, 2014
An adaptive permutation approach for genome-wide association study: evaluation and recommendations for useRonglin Che, John R Jack, Alison A Motsinger-Reif, et al.
Pageof 68