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When estimating power, these refractory data sets were counted as yielding non-significant results.
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For the case of analyzing the refractory cancer data [ 16], gene expression data of 21,073 probes (from Agilent-011521 Human 1A Microarray G4110A) and 113 patient samples (32 different types of refractory cancer) were used in this study.
From the refractory cancer data, 339 contextual gene sets were identified by our context mining based method, and the same number of biclusters were identified using ISA.
This was confirmed by learning a gene set interaction network and identifying tissue-type specificity from the refractory cancer data, with gene sets from both methods.
The comparison to the result using a conventional biclustering-based approach, using a refractory cancer data set, we show the proposed method is much more sensitive in identifying context-specific interactions.
For patients with dysplasia refractory to RFA, data are limited regarding efficacy of endoscopic therapy.
Whereas its usefulness for out-of-hospital cardiac arrest seems poor, extracorporeal cardiopulmonary resuscitation (e-CPR, i.e. veno-arterial extracorporeal membrane oxygenation (VA-ECMO) under cardiopulmonary resuscitation) could potentially be a life-saving strategy for refractory IHCA, but data are missing.
Among this group we identified 22 patients who received a combination of daclizumab and infliximab for steroid-refractory aGVHD; sufficient data was available for 17 of these patients for a detailed review of outcomes.
Consequently, phenotypes are refractory to attempts at data integration that would allow computational analyses across studies and study systems [1].
We identified contextual gene sets and a network of the gene sets from the gene expression data of refractory cancer.
There is a current trend to use short-term support with ECMO in refractory cardiogenic shock but data from large randomized trials are lacking.
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