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Adam McDermaid

Showing results (1-10 of 18) with videos related to

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Mathematical Biosciences|February 16, 2019
Predicting outcomes of chronic kidney disease from EMR data based on Random Forest RegressionJing Zhao, Shaopeng Gu, Adam McDermaid
Bioinformatics (Oxford, England)|April 19, 2017
DMINDA 2.0: integrated and systematic views of regulatory DNA motif identification and analysesJinyu Yang, Xin Chen, Adam McDermaid, et al.
Horticulture Research|November 1, 2019
Differential gene expression in non-transgenic and transgenic "M.26" apple overexpressing a peach CBF gene during the transition from eco-dormancy to bud breakTimothy Artlip, Adam McDermaid, Qin Ma, et al.
Briefings in Bioinformatics|March 24, 2017
An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq dataBingqiang Liu, Jinyu Yang, Yang Li, et al.
Bioinformatics (Oxford, England)|May 23, 2019
MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptomeAnjun Ma, Minxuan Sun, Adam McDermaid, et al.
Briefings in Bioinformatics|August 13, 2018
Interpretation of differential gene expression results of RNA-seq data: review and integrationAdam McDermaid, Brandon Monier, Jing Zhao, et al.
Trends in Biotechnology|August 21, 2020
Integrative Methods and Practical Challenges for Single-Cell Multi-omicsAnjun Ma, Adam McDermaid, Jennifer Xu, et al.
Bioinformatics (Oxford, England)|October 4, 2019
MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptomeAnjun Ma, Minxuan Sun, Adam McDermaid, et al.
Briefings in Bioinformatics|May 9, 2017
Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbesSheng-Yong Niu, Jinyu Yang, Adam McDermaid, et al.
Briefings in Bioinformatics|February 27, 2018
Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbesSheng-Yong Niu, Jinyu Yang, Adam McDermaid, et al.
Pageof 2

Showing results (1-10 of 18) with videos related to

Sort By:
Pageof 2
Mathematical Biosciences|February 16, 2019
Predicting outcomes of chronic kidney disease from EMR data based on Random Forest RegressionJing Zhao, Shaopeng Gu, Adam McDermaid
Bioinformatics (Oxford, England)|April 19, 2017
DMINDA 2.0: integrated and systematic views of regulatory DNA motif identification and analysesJinyu Yang, Xin Chen, Adam McDermaid, et al.
Horticulture Research|November 1, 2019
Differential gene expression in non-transgenic and transgenic "M.26" apple overexpressing a peach CBF gene during the transition from eco-dormancy to bud breakTimothy Artlip, Adam McDermaid, Qin Ma, et al.
Briefings in Bioinformatics|March 24, 2017
An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq dataBingqiang Liu, Jinyu Yang, Yang Li, et al.
Bioinformatics (Oxford, England)|May 23, 2019
MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptomeAnjun Ma, Minxuan Sun, Adam McDermaid, et al.
Briefings in Bioinformatics|August 13, 2018
Interpretation of differential gene expression results of RNA-seq data: review and integrationAdam McDermaid, Brandon Monier, Jing Zhao, et al.
Trends in Biotechnology|August 21, 2020
Integrative Methods and Practical Challenges for Single-Cell Multi-omicsAnjun Ma, Adam McDermaid, Jennifer Xu, et al.
Bioinformatics (Oxford, England)|October 4, 2019
MetaQUBIC: a computational pipeline for gene-level functional profiling of metagenome and metatranscriptomeAnjun Ma, Minxuan Sun, Adam McDermaid, et al.
Briefings in Bioinformatics|May 9, 2017
Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbesSheng-Yong Niu, Jinyu Yang, Adam McDermaid, et al.
Briefings in Bioinformatics|February 27, 2018
Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbesSheng-Yong Niu, Jinyu Yang, Adam McDermaid, et al.
Pageof 2