Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive Power
Anthony Culos, Amy S. Tsai, Natalie Stanley, Martin Becker, Mohammad Sajjad Ghaemi, David R. McIlwain, Ramin Fallahzadeh, Athena Tanada, Huda Nassar, Edward A. Ganio, Laura S. Peterson, Xiaoyuan Han, Ina Annelies Stelzer, Kazuo Ando, Dyani Kalea Gaudilliere, , Nima Aghaeepour
The paper introduces a machine learning method that integrates immunological knowledge to improve predictive power from mass cytometry data.
bioRxiv · Feb 26, 2020 · PreprintBioinformatics