Patients with blood disorders, can be treated by stem cell transplants from a third party. Finding an adult match for such patients is not always possible, but alternatives such as umbilical cord blood (UCB) can be used for transplantation. UCB are readily available and stored in frozen cell banks around the world. However, UCB transplants show delayed and, sometimes, insufficient engraftment of the patient's haematopoietic system. In this study, we will investigate characteristics of UCB from different donors to find biomarkers, which are associated with better engraftment in a pre-clinical animal model and in patients who received UCB transplants. We will employ cutting-edge cellular and molecular biology analyses and implement in-depth artificial intelligence (machine learning) methodology in order to find the biomarkers and develop robust test for selection of UCB units, which would work best in patients and reduce the number of failed transplants.