Identifying pathogenic processes by integrating microarray data with prior knowledge

BMC Bioinformatics

Table 3 Comparing performance of our method (MCIP) with and without the use of priors to k -means clustering

The performances are obtained by evaluating the result clusters against a literature based reference network comprising pairs of genes co-cited in Pubmed articles with the Medical Subject Headings (MeSH) left ventricular hypertrophy (for the heart failure data) and melanoma cancer (for the melanoma cancer data). Sens.=sensitivity, Spec. = specificity, PPV = Positive predictive value, AUC = Area under receiver operator curve, and K = number of clusters, which is automatically found by our method, and by using the Gap index for k-means clustering.

ISSN: 1471-2105