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Lin S Chen

Showing results (1-10 of 53) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|May 9, 2012
Using eQTLs to reconstruct gene regulatory networksLin S Chen
Bioinformatics (Oxford, England)|August 23, 2008
Eigen-R2 for dissecting variation in high-dimensional studiesLin S Chen, John D Storey
Genetic Epidemiology|March 8, 2013
Marbled inflation from population structure in gene-based association studies with rare variantsQianying Liu, Dan L Nicolae, Lin S Chen
Biometrics|January 30, 2014
A penalized EM algorithm incorporating missing data mechanism for Gaussian parameter estimationLin S Chen, Ross L Prentice, Pei Wang
Genetic Epidemiology|April 9, 2021
A robust two-sample transcriptome-wide Mendelian randomization method integrating GWAS with multi-tissue eQTL summary statisticsKevin J Gleason, Fan Yang, Lin S Chen
NAR Genomics and Bioinformatics|March 3, 2020
IGREX for quantifying the impact of genetically regulated expression on phenotypesMingxuan Cai, Lin S Chen, Jin Liu, et al.
Nature Communications|October 31, 2022
Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiologyQing Cheng, Xiao Zhang, Lin S Chen, et al.
The Annals of Applied Statistics|May 11, 2018
A MIXED-EFFECTS MODEL FOR INCOMPLETE DATA FROM LABELING-BASED QUANTITATIVE PROTEOMICS EXPERIMENTSLin S Chen, Jiebiao Wang, Xianlong Wang, et al.
Genome Biology|October 13, 2007
Harnessing naturally randomized transcription to infer regulatory relationships among genesLin S Chen, Frank Emmert-Streib, John D Storey
Biostatistics (Oxford, England)|June 26, 2018
Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingnessJiebiao Wang, Pei Wang, Donald Hedeker, et al.
Pageof 6

Showing results (1-10 of 53) with videos related to

Sort By:
Pageof 6
Methods in Molecular Biology (Clifton, N.J.)|May 9, 2012
Using eQTLs to reconstruct gene regulatory networksLin S Chen
Bioinformatics (Oxford, England)|August 23, 2008
Eigen-R2 for dissecting variation in high-dimensional studiesLin S Chen, John D Storey
Genetic Epidemiology|March 8, 2013
Marbled inflation from population structure in gene-based association studies with rare variantsQianying Liu, Dan L Nicolae, Lin S Chen
Biometrics|January 30, 2014
A penalized EM algorithm incorporating missing data mechanism for Gaussian parameter estimationLin S Chen, Ross L Prentice, Pei Wang
Genetic Epidemiology|April 9, 2021
A robust two-sample transcriptome-wide Mendelian randomization method integrating GWAS with multi-tissue eQTL summary statisticsKevin J Gleason, Fan Yang, Lin S Chen
NAR Genomics and Bioinformatics|March 3, 2020
IGREX for quantifying the impact of genetically regulated expression on phenotypesMingxuan Cai, Lin S Chen, Jin Liu, et al.
Nature Communications|October 31, 2022
Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiologyQing Cheng, Xiao Zhang, Lin S Chen, et al.
The Annals of Applied Statistics|May 11, 2018
A MIXED-EFFECTS MODEL FOR INCOMPLETE DATA FROM LABELING-BASED QUANTITATIVE PROTEOMICS EXPERIMENTSLin S Chen, Jiebiao Wang, Xianlong Wang, et al.
Genome Biology|October 13, 2007
Harnessing naturally randomized transcription to infer regulatory relationships among genesLin S Chen, Frank Emmert-Streib, John D Storey
Biostatistics (Oxford, England)|June 26, 2018
Using multivariate mixed-effects selection models for analyzing batch-processed proteomics data with non-ignorable missingnessJiebiao Wang, Pei Wang, Donald Hedeker, et al.
Pageof 6