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Figure 2 | Algorithms for Molecular Biology

Figure 2

From: Characteristics of predictor sets found using differential prioritization

Figure 2

Plots of α M MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFXoqydaqhaaWcbaGaemyta0eabaGaey4fIOcaaaaa@3091@ vs. K. The DDP producing the optimal separation of classes as measured using the Manhattan distance, α M MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFXoqydaqhaaWcbaGaemyta0eabaGaey4fIOcaaaaa@3091@ , as a function of K for toy datasets generated from (a) the OVA model and (b) the PW model. Each of the five panels in (a) and (b) represents a plot from toy datasets generated using a different value of G (a parameter which denotes the number of genes in each group of marker genes and is set during the generation of the toy datasets).

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