The UNC Computational Medicine Program and the UNC School of Medicine Office of Research has selected three teams to receive the inaugural round of Computational Medicine Pilot Grant Awards.

The program sought collaborative proposals from research areas in cognitive computing/machine learning; image analysis/computer vision; computational and mathematical modeling; bioinformatics and computational genomics; health informatics and network analysis.

Three winning teams were selected from a large pool of applicants whose proposals embodied the programs goals, seeking to integrate modern computational approaches with cutting edge experimental techniques to advance the goal of predictive health care:

“Computational-Enabled Design of Engineered Vascular Tissues for Ischemic Disease”

  • Co-PI: Boyce E. Griffith, Department of Mathematics and Applied Physical Sciences and Biomedical Engineering
  • Co-PI: William J. Polacheck, Department of Biomedical Engineering in Biomedical Microdevices

This team’s research objective is to apply methods of computational mechanics and fluid dynamics to determine pressures and shear stresses in imaged-based models of engineered vascular networks. With this pilot award they aim to collect preliminary data on that will be used to establish initial computational models, which will serve as preliminary data for future funding applications.

“Single-Cell Omics Analyses for Assessing Genomic, Transcriptomic, and Epigenomic Heterogeneity in Cancer,”

  • Co-PI: Yuchao Jiang, Department of Biostatistics, Department of Genetics
  • Co-Pi: Qing Zhang, Department of Pathology and Laboratory Medicine

This team’s research objectives are to develop new statistical methods and computational algorithms for single-cell omics analyses to assess genomic, transcriptomic, and epigenomic heterogeneity in tumors. Their goal is to use the methods developed as part of this pilot award to facilitate our understanding of tumor progression and metastasis, aid biomarker discovery for diagnosis, and tailor personalized treatment. Jian and Zhang are UNC Lineberger members.

“Breast Cancer Molecular Subtype Prediction from Stationary Digital breast Tomosysnthesis Imaging”

  • PI: Yueh Lee, Department of Radiology in Neuroradiology, Biomedical Engineering and Physics
  • Co-PI: Marc Niethammer, Department of Computer Science, Biomedical Research Imaging Center
  • Co-PI: Cherie Kuzmiak, Department of Radiology – Breast Imaging Research Lab
  • Co-PI: Melissa Troester, Department of Epidemiology, Department of Pathology and Laboratory Medicine
  • Co-PI: Stephanie Downs-Canner, Department of Surgery Division of Surgical Oncology
  • Co-PI: Kristalyn Gallagher, Department of Surgery Division of Surgical Oncology
  • Co-PI: Benjamin Calhoun, Department of Pathology and Laboratory Medicine,
  • Co-PI: Otto Zhou, Department of Physics and Astronomy; Clinical Research, Breast Cancer

This team’s research objective is to compare the abilities of Stationary Digital Breast Tomosynthesis (s-DBT), Digital Breast Tomosynthesis (DBT), and mammography to predict molecular subtypes of breast cancer. With this pilot award they aim to potentially improve the accuracy while reducing the costs for evaluating cancer subtypes and to serve as a stepping stone for both machine learning algorithm development and the development of our next generation stationary digital breast tomosynthesis devices. Lee, Kuzmiak, Troester, Calhoun and Zhou are UNC Lineberger members.