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BioData mining

Showing results (151-160 of 671) with videos related to

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Biodata Mining|June 19, 2026
Large-scale transcriptomic data mining using explainable XGBoost and SHAP reveals shared biomarkers and molecular mechanisms between type-2 diabetes and triple-negative breast cancer for drug repurposingMd Feroj Ahmed, Ovi Sharma, Tasfia Noor, et al.
Biodata Mining|June 26, 2026
Learning a distance for the clustering of patients with amyotrophic lateral sclerosisGuillaume Tejedor Y Dominguez, Hugo Alarcan, Veronika Peralta, et al.
Biodata Mining|December 20, 2014
Motif mining based on network space compressionQiang Zhang, Yuan Xu
Biodata Mining|November 11, 2014
Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trendsEmad A Mohammed, Behrouz H Far, Christopher Naugler
Biodata Mining|April 8, 2016
Detecting gene-gene interactions using a permutation-based random forest methodJing Li, James D Malley, Angeline S Andrew, et al.
Biodata Mining|December 1, 2015
Genome-wide predictors of NF-κB recruitment and transcriptional activityMarcin Cieślik, Stefan Bekiranov
Biodata Mining|March 8, 2016
Robust normalization protocols for multiplexed fluorescence bioimage analysisShan E Ahmed Raza, Daniel Langenkämper, Korsuk Sirinukunwattana, et al.
Biodata Mining|December 23, 2015
A significant risk locus on 19q13 for bipolar disorder identified using a combined genome-wide linkage and copy number variation analysisMagnus Lekman, Robert Karlsson, Lisette Graae, et al.
Biodata Mining|December 24, 2015
Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networksTing Hu, Angeline S Andrew, Margaret R Karagas, et al.
Biodata Mining|January 29, 2016
The prediction accuracy of dynamic mixed-effects models in clustered dataBrian S Finkelman, Benjamin French, Stephen E Kimmel
Pageof 68

Showing results (151-160 of 671) with videos related to

Sort By:
Pageof 68
Biodata Mining|June 19, 2026
Large-scale transcriptomic data mining using explainable XGBoost and SHAP reveals shared biomarkers and molecular mechanisms between type-2 diabetes and triple-negative breast cancer for drug repurposingMd Feroj Ahmed, Ovi Sharma, Tasfia Noor, et al.
Biodata Mining|June 26, 2026
Learning a distance for the clustering of patients with amyotrophic lateral sclerosisGuillaume Tejedor Y Dominguez, Hugo Alarcan, Veronika Peralta, et al.
Biodata Mining|December 20, 2014
Motif mining based on network space compressionQiang Zhang, Yuan Xu
Biodata Mining|November 11, 2014
Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trendsEmad A Mohammed, Behrouz H Far, Christopher Naugler
Biodata Mining|April 8, 2016
Detecting gene-gene interactions using a permutation-based random forest methodJing Li, James D Malley, Angeline S Andrew, et al.
Biodata Mining|December 1, 2015
Genome-wide predictors of NF-κB recruitment and transcriptional activityMarcin Cieślik, Stefan Bekiranov
Biodata Mining|March 8, 2016
Robust normalization protocols for multiplexed fluorescence bioimage analysisShan E Ahmed Raza, Daniel Langenkämper, Korsuk Sirinukunwattana, et al.
Biodata Mining|December 23, 2015
A significant risk locus on 19q13 for bipolar disorder identified using a combined genome-wide linkage and copy number variation analysisMagnus Lekman, Robert Karlsson, Lisette Graae, et al.
Biodata Mining|December 24, 2015
Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networksTing Hu, Angeline S Andrew, Margaret R Karagas, et al.
Biodata Mining|January 29, 2016
The prediction accuracy of dynamic mixed-effects models in clustered dataBrian S Finkelman, Benjamin French, Stephen E Kimmel
Pageof 68