News From the Field
Neural nets supplant marker genes in analyzing single cell RNA sequencing
November 13, 2018
This material is available primarily for archival purposes. Telephone numbers or other contact information may be out of date; please see current contact information at media contacts.Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have been studied using single cell RNA-sequencing. This finding, published in the online journal Nature Communications, could help researchers identify new cell subtypes and differentiate between healthy and diseased cells. Full Story
Carnegie Mellon University
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