Nten  Nyiam

Nten Nyiam

Scholar Title

Eric and Wendy Schmidt Center Funded Research and Innovation Scholar

Research Title

Application of Spatial Transcriptomics to Ovarian Cancer




Electrical Engineering and Computer Science

Research Areas
  • Computational Biology

Caroline Uhler


Spatial transcriptomics is a molecular profiling method that uses mRNA expression data to assign cell types to their locations in histological sections. This allows researchers to measure all gene activity in a tissue sample and map where that activity is occurring. The goal of this project is to apply spatial transcriptomics to a clinical trial being run on ovarian cancer patients. There has been variability in the outcomes of patients: some experience complete remission while others experience recurrence. We believe that, by encoding spatial information in a graph and combining it with expression data and using a graph neural network to get an output representation, we can shed light on this variability by detecting patterns differentiating the two groups of patients.


I am participating in SuperUROP because I want to gain further experience with computational biology, especially from a machine learning lens. I am excited to apply the knowledge I gained from 6.047 and 18.418 to my project and to leverage a method as powerful and relevant as spatial transcriptomics.

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