{"rating_data": {"avg_stars": 0, "total": 0, "avg": 0}, "name": "BreastMark (NOTE: plugin can take ~2 mins to load)", "created": "2013-08-17 01:14:47", "url": "http://glados.ucd.ie/BreastMark/post_gene_default.cgi?name={{EntrezGene}}&DFS=RFS&median=median&lymph_positive=positive&lymph_negative=negative&LumA_pam50=LumA_pam50&LumB_pam50=LumB_pam50&Her2_pam50=Her2_pam50", "lastmodified": "2013-08-17 01:14:48", "usage_data": {"layouts": 0.0, "users": 0}, "popularity": 0.0, "owner": {"username": "asu", "url": "/profile/3/asu", "name": "Andrew Su"}, "species": ["human"], "shortUrl": "glados.ucd.ie", "id": 1125, "short_description": "identify subsets of genes/miRNAs that are associated with disease progression in breast cancer and its subtypes", "role_permission": ["biogpsusers"], "permission_style": "public", "type": "iframe", "options": null, "description": "BreastMark is an algorithm we have developed that has allowed us to identify subsets of genes/miRNAs that are associated with disease progression in breast cancer and its subtypes i.e. a set of putative prognostic markers. This algorithm integrates gene expression microarrays which frequently also contain miRNA expression information, and detailed clinical data to correlate clinical outcome with differential gene/miRNA expression levels. This algorithm integrates gene expression and survival data from 26 datasets on 12 different microarray platforms corresponding to ~17,000 genes in up to 4,738 samples. It also allows us to examine the prognostic potential of 341 microRNAs. The accompanying manuscript is published and available here: https://www.ncbi.nlm.nih.gov/pubmed/23820017. \n"}