Elena Dimitrova

The paper uses neural networks with topological data analysis to classify human induced pluripotent stem cell colonies by treatment condition, achieving performance comparable to ResNet.

This paper introduces a computational pipeline using topological data analysis to quantify multicellular patterning in human induced pluripotent stem cell colonies, revealing subtle differences in differentiation stages.

This study compares temporal deep learning models for classifying sequences of cell colony images to understand cellular state transitions.