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Kenong Su

Showing results (1-10 of 9) with videos related to

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Frontiers in Genetics|April 26, 2021
Non-linear Normalization for Non-UMI Single Cell RNA-SeqZhijin Wu, Kenong Su, Hao Wu
Bioinformatics (Oxford, England)|July 3, 2020
Simulation, power evaluation and sample size recommendation for single-cell RNA-seqKenong Su, Zhijin Wu, Hao Wu
Briefings in Bioinformatics|February 21, 2021
Accurate feature selection improves single-cell RNA-seq cell clusteringKenong Su, Tianwei Yu, Hao Wu
Genome Biology|September 10, 2021
Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference constructionWenjing Ma, Kenong Su, Hao Wu
Cell Reports Methods|October 21, 2021
Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosisKenong Su, Qi Yu, Ronglai Shen, et al.
Nature Machine Intelligence|March 6, 2023
A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputationJustin Lakkis, Amelia Schroeder, Kenong Su, et al.
Human Molecular Genetics|August 10, 2022
Cell type-specific DNA methylome signatures reveal epigenetic mechanisms for neuronal diversity and neurodevelopmental disorderYulin Jin, Kenong Su, Ha Eun Kong, et al.
Genome Biology|December 27, 2022
NetAct: a computational platform to construct core transcription factor regulatory networks using gene activityKenong Su, Ataur Katebi, Vivek Kohar, et al.
Cell Stem Cell|March 7, 2020
Sliced Human Cortical Organoids for Modeling Distinct Cortical Layer FormationXuyu Qian, Yijing Su, Christopher D Adam, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Frontiers in Genetics|April 26, 2021
Non-linear Normalization for Non-UMI Single Cell RNA-SeqZhijin Wu, Kenong Su, Hao Wu
Bioinformatics (Oxford, England)|July 3, 2020
Simulation, power evaluation and sample size recommendation for single-cell RNA-seqKenong Su, Zhijin Wu, Hao Wu
Briefings in Bioinformatics|February 21, 2021
Accurate feature selection improves single-cell RNA-seq cell clusteringKenong Su, Tianwei Yu, Hao Wu
Genome Biology|September 10, 2021
Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference constructionWenjing Ma, Kenong Su, Hao Wu
Cell Reports Methods|October 21, 2021
Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosisKenong Su, Qi Yu, Ronglai Shen, et al.
Nature Machine Intelligence|March 6, 2023
A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputationJustin Lakkis, Amelia Schroeder, Kenong Su, et al.
Human Molecular Genetics|August 10, 2022
Cell type-specific DNA methylome signatures reveal epigenetic mechanisms for neuronal diversity and neurodevelopmental disorderYulin Jin, Kenong Su, Ha Eun Kong, et al.
Genome Biology|December 27, 2022
NetAct: a computational platform to construct core transcription factor regulatory networks using gene activityKenong Su, Ataur Katebi, Vivek Kohar, et al.
Cell Stem Cell|March 7, 2020
Sliced Human Cortical Organoids for Modeling Distinct Cortical Layer FormationXuyu Qian, Yijing Su, Christopher D Adam, et al.
Pageof 1