| Cox-nnet: an artificial neural network method for prognosis prediction of high-throughput omics data T Ching, X Zhu, LX Garmire PLoS computational biology 14 (4), e1006076, 2018 | 426 | 2018 |
| DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data C Arisdakessian, O Poirion, B Yunits, X Zhu, LX Garmire Genome biology 20, 1-14, 2019 | 277 | 2019 |
| Analysis of the human protein atlas image classification competition W Ouyang, CF Winsnes, M Hjelmare, AJ Cesnik, L Åkesson, H Xu, ... Nature methods 16 (12), 1254-1261, 2019 | 133 | 2019 |
| Single-cell transcriptomics bioinformatics and computational challenges OB Poirion, X Zhu, T Ching, L Garmire Frontiers in genetics 7, 163, 2016 | 133 | 2016 |
| Time Series miRNA-mRNA integrated analysis reveals critical miRNAs and targets in macrophage polarization L Lu, S McCurdy, S Huang, X Zhu, K Peplowska, M Tiirikainen, ... Scientific reports 6 (1), 37446, 2016 | 94 | 2016 |
| Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization X Zhu, T Ching, X Pan, SM Weissman, L Garmire PeerJ 5, e2888, 2017 | 92 | 2017 |
| Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists X Zhu, TK Wolfgruber, A Tasato, C Arisdakessian, DG Garmire, ... Genome medicine 9, 1-12, 2017 | 81 | 2017 |
| Using single-cell multiple omics approaches to resolve tumor heterogeneity MA Ortega, O Poirion, X Zhu, S Huang, TK Wolfgruber, R Sebra, ... Clinical and translational medicine 6, 1-16, 2017 | 80 | 2017 |
| Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage O Poirion, X Zhu, T Ching, LX Garmire Nature communications 9 (1), 4892, 2018 | 68 | 2018 |
| mirMark: a site-level and UTR-level classifier for miRNA target prediction M Menor, T Ching, X Zhu, D Garmire, LX Garmire Genome biology 15, 1-16, 2014 | 59 | 2014 |
| Single cell transcriptomics reveals unanticipated features of early hematopoietic precursors J Yang, Y Tanaka, M Seay, Z Li, J Jin, LX Garmire, X Zhu, A Taylor, W Li, ... Nucleic acids research 45 (3), 1281-1296, 2017 | 52 | 2017 |
| Pan-cancer analyses reveal long intergenic non-coding RNAs relevant to tumor diagnosis, subtyping and prognosis T Ching, K Peplowska, S Huang, X Zhu, Y Shen, J Molnar, H Yu, ... EBioMedicine 7, 62-72, 2016 | 41 | 2016 |
| Deep learning predicts interval and screening-detected cancer from screening mammograms: a case-case-control study in 6369 women X Zhu, TK Wolfgruber, L Leong, M Jensen, C Scott, S Winham, ... Radiology 301 (3), 550-558, 2021 | 31 | 2021 |
| Meta-dimensional data integration identifies critical pathways for susceptibility, tumorigenesis and progression of endometrial cancer R Wei, I De Vivo, S Huang, X Zhu, H Risch, JH Moore, H Yu, LX Garmire Oncotarget 7 (34), 55249, 2016 | 19 | 2016 |
| GranatumX: a community-engaging, modularized, and flexible webtool for single-cell data analysis DG Garmire, X Zhu, A Mantravadi, Q Huang, B Yunits, Y Liu, T Wolfgruber, ... Genomics, Proteomics and Bioinformatics 19 (3), 452-460, 2021 | 10* | 2021 |
| Maternal cardiovascular-related single nucleotide polymorphisms, genes, and pathways associated with early-onset preeclampsia P Benny, K Yamasato, B Yunits, X Zhu, T Ching, LX Garmire, MJ Berry, ... PLoS One 14 (9), e0222672, 2019 | 10 | 2019 |
| Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage. Nat Commun. 2018; 9 (1): 4892 O Poirion, X Zhu, T Ching, LX Garmire | 6 | 2019 |
| Using single nucleotide variations in single-cell RNA-seq to identify tumor subpopulations and genotype-phenotype linkage. bioRxiv OB Poirion, X Zhu, T Ching, LX Garmire bioRxiv, 095810, 2017 | 4 | 2017 |
| Data Analysis in Single-Cell RNA-Seq X Zhu, LX Garmire Single-Cell Omics, 419-432, 2019 | 2 | 2019 |
| Author correction: analysis of the human protein atlas image classification competition W Ouyang, CF Winsnes, M Hjelmare, AJ Cesnik, L Åkesson, H Xu, ... Nature Methods 17 (9), 948, 2020 | 1 | 2020 |
Lana GarmireUniversity of MichiganE-mailová adresa ověřena na: med.umich.edu