Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data von Ching, Travers, Zhu, Xun, Garmire, Lana X

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DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data von Arisdakessian, Cédric, Poirion, Olivier, Yunits, Breck, Zhu, Xun, Garmire, Lana X

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Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer von Chaudhary, Kumardeep, Poirion, Olivier B, Lu, Liangqun, Garmire, Lana X

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Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data von Alakwaa, Fadhl M, Chaudhary, Kumardeep, Garmire, Lana X

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Power analysis and sample size estimation for RNA-Seq differential expression von Ching, Travers, Huang, Sijia, Garmire, Lana X

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Mentorship is not co-authorship: a revisit to mentorship von Garmire, Lana X.

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DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data von Poirion, Olivier B., Jing, Zheng, Chaudhary, Kumardeep, Huang, Sijia, Garmire, Lana X.

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From Hawaii to PECASE award: tips of success from a female bioinformatician von Garmire, Lana X

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Blood-derived lncRNAs as biomarkers for cancer diagnosis: the Good, the Bad and the Beauty von Badowski, Cedric, He, Bing, Garmire, Lana X.

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Evaluation of Cell Type Annotation R Packages on Single-cell RNA-seq Data von Huang, Qianhui, Liu, Yu, Du, Yuheng, Garmire, Lana X.

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Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage von Poirion, Olivier, Zhu, Xun, Ching, Travers, Garmire, Lana X.

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ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs von He, Bing, Xiao, Yao, Liang, Haodong, Huang, Qianhui, Du, Yuheng, Li, Yijun, Garmire, David, Sun, Duxin, Garmire, Lana X.

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Regulated Accumulation of Desmosterol Integrates Macrophage Lipid Metabolism and Inflammatory Responses von Spann, Nathanael J., Garmire, Lana X., McDonald, Jeffrey G., Myers, David S., Milne, Stephen B., Shibata, Norihito, Reichart, Donna, Fox, Jesse N., Shaked, Iftach, Heudobler, Daniel, Raetz, Christian R.H., Wang, Elaine W., Kelly, Samuel L., Sullards, M. Cameron, Murphy, Robert C., Merrill, Alfred H., Brown, H. Alex, Dennis, Edward A., Li, Andrew C., Ley, Klaus, Tsimikas, Sotirios, Fahy, Eoin, Subramaniam, Shankar, Quehenberger, Oswald, Russell, David W., Glass, Christopher K.

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Enter the Matrix: Factorization Uncovers Knowledge from Omics von Stein-O’Brien, Genevieve L., Arora, Raman, Culhane, Aedin C., Favorov, Alexander V., Garmire, Lana X., Greene, Casey S., Goff, Loyal A., Li, Yifeng, Ngom, Aloune, Ochs, Michael F., Xu, Yanxun, Fertig, Elana J.

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Evaluation of STAR and Kallisto on Single Cell RNA-Seq Data Alignment von Du, Yuheng, Huang, Qianhui, Arisdakessian, Cedric, Garmire, Lana X.

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More Is Better: Recent Progress in Multi-Omics Data Integration Methods von Huang, Sijia, Chaudhary, Kumardeep, Garmire, Lana X

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A review of omics approaches to study preeclampsia von Benny, Paula A., Alakwaa, Fadhl M., Schlueter, Ryan J., Lassiter, Cameron B., Garmire, Lana X.

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Multimodal Meta-Analysis of 1,494 Hepatocellular Carcinoma Samples Reveals Significant Impact of Consensus Driver Genes on Phenotypes von Chaudhary, Kumardeep, Poirion, Olivier B, Lu, Liangqun, Huang, Sijia, Ching, Travers, Garmire, Lana X

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A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer von Huang, Sijia, Yee, Cameron, Ching, Travers, Yu, Herbert, Garmire, Lana X

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Computational Methods for Single-cell Multi-omics Integration and Alignment von Stanojevic, Stefan, Li, Yijun, Ristivojevic, Aleksandar, Garmire, Lana X.

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