Wuming Gong, PhD

Assistant Professor of Medicine, Cardiology

Wuming Gong

Contact Info

Mailing Address:
420 Delaware Street SE
MMC 508
Minneapolis, MN 55455

Assistant Professor of Medicine, Cardiology

PhD, University of Minnesota, Minneapolis, MN


Awards & Recognition

  • Graduate School Block Grant and Tuition Fellowship, University of Minnesota (2007 - 2008)
  • Grand prize winner of Minnesota Supercomputing Institute Research Exhibition (2014)
  • Winner team of the Allen Institute Cell Lineage Reconstruction DREAM Challenge 2 (2020)
  • Winner team of the Allen Institute Cell Lineage Reconstruction DREAM Challenge 3 (2020)


Research Summary/Interests

I have a broad background in cardiovascular developmental biology, bioinformatics and computational biology, with specific training and expertise in database constructions, data analysis and algorithm development. I was trained in genetics and genomics, and have more than ten years of experience on bioinformatics and computational biology, including siRNA design, peptide array design, database construction and predicting development related genes. After I joined the Lillehei Heart Institute, I mainly focused on developing algorithms for single cell RNA-seq analysis including tools such as dpath (prediction of cell differentiation), TCM (visualization of temporal scRNA-seq data), DrImpute (imputing dropout events in the scRNA-seq data), DCLEAR (CRSPR/cas9-based single cell lineage reconstruction), and inferring gene regulatory networks from multi-dimensional omics- data. In addition, I have successfully collaborated with other investigators on the characterization of novel genes, microRNAs, long noncoding RNAs (lncRNAs) that have important functions in various biological processes. In addition, my laboratory has expertise using and analyzing large datasets focused on proteomics, metabolomics and transcriptomics. Combining the large scale genomic approaches with novel machine learning methods, we have recently deciphered the cell populations and defining pathways that are critical for hemato-endothelial development, cardiogenesis and cardiac regeneration. We will further employ these computational biological approaches to amplify and accelerate the research in heart development and cardiovascular disease.


  • Gong W, Granados A, Hu J, Jones M, Raz O, Martinez IS, Zhang H, Chow KK, Kwak IY, Retkute R, Prusokas A, Prusokas A, Khodaverdian A, Zhang R, Wang R, RaoS, Rennert P, Saipradeep V, Naveen S, Joseph T, Rao A, Srinivasan R, Peng J, Han L, Shang X, Garry DJ, Yu T, Chung V, Mason M, Liu Z, Guan Y, Yosef N, Shendure J, Telford M, Shapiro E, Elowitz MB, Meyer P. Benchmarked approaches for cell lineage reconstructions of in vitro dividing cells and in silico models of Caenorhabditis elegans and Mus musculus developmental trees. Cell Systems. 2021 Aug 18;12(8):810-826.e4
  • Gong W, Kwak IY, Koyano-Nakagawa N, Pan W, Garry DJ. TCM visualizes trajectories and cell populations from single cell data. Nat Commun2018 Jul 16;9(1):2749
  • Gong W, Kwak IY, Pota P, Koyano-Nakagawa N, Garry DJ. DrImpute: Imputing dropout events in single cell RNA sequencing data. BMC Bioinformatics2018 Jun 8;19(1):220.
  • Gong W, Rasmussen TL, Singh BN, Koyano-Nakagawa N, Pan W, Garry DJ. Dpath software reveals hierarchical haemato-endothelial lineages of Etv2 progenitors based on single-cell transcriptome analysis. Nat Commun 2017; 8: 14362 
  • Gong W, Koyano-Nakagawa N, Li T, Garry DJ. Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data. BMC Bioinformatics. 2015, 16:74.