Evan Biederstedt

Oct 10, 2023 | biorxiv.org | Felix R. Fischer |David Fischer |Evan Biederstedt |Alexandra-Chloé Villani

AbstractIdentifying cellular identities (both novel and well-studied) is one of the key use cases in single-cell transcriptomics. While supervised machine learning has been leveraged to automate cell annotation predictions for some time, there has been relatively little progress both in scaling neural networks to large data sets and in constructing models that generalize well across diverse tissues and biological contexts up to whole organisms.