The model's innovative approach lies in its rank value encoding methodology. Instead of processing raw gene expression counts, each cell's genetic profile gets transformed into a prioritized gene list based on relative expression levels normalized across the entire training dataset. This technique minimizes the influence of consistently expressed maintenance genes while highlighting regulatory genes like transcription factors that demonstrate significant variation across cellular conditions—even when their absolute expression remains low. The method also demonstrates enhanced resistance to technical batch variations since internal gene rankings prove more consistent than absolute measurement values.
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05:25, 9 марта 2026Мир