Machine-Learning Ranking
The analysis used Laplace, linear, and radial basis function ranking methods. Lower rank values are interpreted as stronger evidence for possible ASCL2-X synergy before treatment and joint down-regulation after drug exposure. The ranking f…
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The analysis used Laplace, linear, and radial basis function ranking methods. Lower rank values are interpreted as stronger evidence for possible ASCL2-X synergy before treatment and joint down-regulation after drug exposure. The ranking framework used SVM-rank software from Joachims. A previously developed machine-learning search engine ranks gene or protein combinations in signaling pathways. Majority voting across ranking methods was used to identify plausible unexplored ASCL2-X combinations.