Data sets for classification of PBMC using supervised machine learning

The datasets in this Web Page were used in the study "Artificial Neural Networks for classification of single cell gene expression". This study is a part of collaborative research "Supervised Machine Learning for Single Cell Transcriptomics". The collaborators on this project come from the University of Nottingham Ningbo China, HiLab at Metropolitan College - Boston University, Translational Immuno-Genomics Lab at Dana-Farber Cancer Institute/Harvard Medical School, and School of Life Sciences and Technology at Tongji University.

If you use these data sets, please cite:
Shaikh RA, Zhong J, Lyu M, Lin S, Keskin D, Zhang G, Chitkushev L, Brusic V. Classification of Five Cell Types from PBMC Samples using Single Cell Transcriptomics and Artificial Neural Networks. In IEEE Int. Conf. Bioinformatics Biomed. 2019, 2207-2213.