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Giovanni Parmigiani

Showing results (51-60 of 245) with videos related to

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Biostatistics (Oxford, England)|December 18, 2025
Multi-study R-learner for estimating heterogeneous treatment effects across studies using statistical machine learningCathy Shyr, Boyu Ren, Prasad Patil, et al.
Annals of Statistics|May 6, 2017
MODELING DEPENDENT GENE EXPRESSIONDonatello Telesca, Peter Müller, Giovanni Parmigiani, et al.
Biotechniques|April 1, 2003
Statistical modeling and visualization of molecular profiles in cancerRobert Scharpf, Elizabeth S Garrett, Jiang Hu, et al.
Statistics in Medicine|February 24, 2024
Optimal ensemble construction for multistudy prediction with applications to mortality estimationGabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder, et al.
Biometrics|February 18, 2017
Bayesian response-adaptive designs for basket trialsSteffen Ventz, William T Barry, Giovanni Parmigiani, et al.
BMC Bioinformatics|December 13, 2007
Penalized likelihood for sparse contingency tables with an application to full-length cDNA librariesCorinne Dahinden, Giovanni Parmigiani, Mark C Emerick, et al.
Statistics in Medicine|April 15, 2008
Multiple diseases in carrier probability estimation: accounting for surviving all cancers other than breast and ovary in BRCAPROHormuzd A Katki, Amanda Blackford, Sining Chen, et al.
BMC Genomics|September 2, 2008
Haplotype block partitioning as a tool for dimensionality reduction in SNP association studiesCristian Pattaro, Ingo Ruczinski, Danièle M Fallin, et al.
The Annals of Applied Statistics|July 18, 2009
Hidden Markov models for the assessment of chromosomal alterations using high-throughput SNP arraysRobert B Scharpf, Giovanni Parmigiani, Jonathan Pevsner, et al.
Biometrics|October 6, 2018
Multi-study factor analysisRoberta De Vito, Ruggero Bellio, Lorenzo Trippa, et al.
Pageof 25

Showing results (51-60 of 245) with videos related to

Sort By:
Pageof 25
Biostatistics (Oxford, England)|December 18, 2025
Multi-study R-learner for estimating heterogeneous treatment effects across studies using statistical machine learningCathy Shyr, Boyu Ren, Prasad Patil, et al.
Annals of Statistics|May 6, 2017
MODELING DEPENDENT GENE EXPRESSIONDonatello Telesca, Peter Müller, Giovanni Parmigiani, et al.
Biotechniques|April 1, 2003
Statistical modeling and visualization of molecular profiles in cancerRobert Scharpf, Elizabeth S Garrett, Jiang Hu, et al.
Statistics in Medicine|February 24, 2024
Optimal ensemble construction for multistudy prediction with applications to mortality estimationGabriel Loewinger, Rolando Acosta Nunez, Rahul Mazumder, et al.
Biometrics|February 18, 2017
Bayesian response-adaptive designs for basket trialsSteffen Ventz, William T Barry, Giovanni Parmigiani, et al.
BMC Bioinformatics|December 13, 2007
Penalized likelihood for sparse contingency tables with an application to full-length cDNA librariesCorinne Dahinden, Giovanni Parmigiani, Mark C Emerick, et al.
Statistics in Medicine|April 15, 2008
Multiple diseases in carrier probability estimation: accounting for surviving all cancers other than breast and ovary in BRCAPROHormuzd A Katki, Amanda Blackford, Sining Chen, et al.
BMC Genomics|September 2, 2008
Haplotype block partitioning as a tool for dimensionality reduction in SNP association studiesCristian Pattaro, Ingo Ruczinski, Danièle M Fallin, et al.
The Annals of Applied Statistics|July 18, 2009
Hidden Markov models for the assessment of chromosomal alterations using high-throughput SNP arraysRobert B Scharpf, Giovanni Parmigiani, Jonathan Pevsner, et al.
Biometrics|October 6, 2018
Multi-study factor analysisRoberta De Vito, Ruggero Bellio, Lorenzo Trippa, et al.
Pageof 25