More than a billion people suffer from neurological disorders, and understanding how cells interact in the context of different pathologies could lead to viable medical interventions. To this end, the field requires reliable biological markers to discriminate distinct cell types present in a heterogeneous population.

This study, conducted by MSDS students Erik Langenborg, Kevin Sun and Lingfeng Cao, aimed to validate a novel approach for discovering cell-specific gene sets based on gene expression profiles. 

Distilling these markers is complex, hampered by problems such as the curse of dimensionality when relating large counts of genes to few cell type observations. This research presents a method for overcoming these challenges in a data set of microarray gene expression values. 

Results showed a marked improvement in half of the validation examples, while the other sets were not significantly enriched.

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Erik Langenborg
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Kevin Sun
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Lingfeng Cao
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Abigail Flower
School of Data Science
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Chris Overall
UVA School of Medicine
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