On the Application of Active Learning and Gaussian Processes in Postcryopreservation Cell Membrane Integrity Experiments
This source preferred by Damien Fay
Authors: Fay, D., Norkus, M., Murphy, M.J., Barry, F., ÓLaighin, G. and Kilmartin, L.
Journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Abstract Biological cell cryopreservation permits storage of specimens for future use. Stem cell cryostorage in particular is fast becoming a broadly spread practice due to their potential for use in regenerative medicine. For the optimal cryopreservation process, ultralow temperatures are needed. However, elevated temperatures are often unavoidable in a typical sample handling cycle which in turn negatively affects the postcryopreservation integrity of cells. In this paper, we present an application of active learning using an ...