|Awarded On||November 18, 2021|
|Title||Recruitment of First-Time, Tenure-Track Faculty Members|
|Award Mechanism||Recruitment of First-Time, Tenure-Track Faculty Members|
|Institution/Organization||The University of Texas at Arlington|
|Principal Investigator/Program Director||Jacob Luber|
|Cancer Sites||All Sites|
|Summary of Goals and Objectives||
With the advent of modern-day sequencing, imaging, and spatial proteomics technologies, the rate at which data is being generated in the oncology clinic and at the bench is far surpassing the rate at which the computational resources to process this deluge of data are improving. There exist petabytes of openly available cancer pathology imaging data, both from traditional H&E staining and novel spatially resolved proteomics methods such as CODEX, that contain information that is highly relevant for cancer treatment and therapeutic discovery. In order to leverage this data to improve cancer treatment and drug discovery initiatives, algorithms and machine learning methods that enable it to be efficie...