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- W2352936201 abstract "Using high-throughput microarray data,one important task is to identify differentially expressed genes(DEGs),which would be 'significant' enough for the follow-up studies of disease mechanisms and diagnosis.It is known that DEG lists produced from different studies for a cancer are usually highly inconsistent,raising questions about their biological significance and clinical implication.However,it has been suggested that apparently irreproducible DEGs tend to disturb some similar or the same biological functions.Here,we propose a feasible method to evaluate functional reproducibility using the POGR score,taking advantage of both co-expression and protein interaction relationship.Analyzing two microarray data of ovarian,we found the proposed POGR score of two DEG lists is significantly higher than expected by chance,providing statistical evidence supporting that the underlying molecular assumption is reasonable." @default.
- W2352936201 created "2016-06-24" @default.
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- W2352936201 date "2011-01-01" @default.
- W2352936201 modified "2023-09-28" @default.
- W2352936201 title "Evaluating reproducibility of differential expression genes based on protein-protein interactions" @default.
- W2352936201 hasPublicationYear "2011" @default.
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