GSE16476

Integrated bioinformatic and wet-lab approach to identify potential oncogenic networks in neuroblastoma

mRNA profiles of thousands of human tumors are available, but methods to deduce oncogenic signaling networks from these data lag behind. It is especially challenging to identify main-regulatory routes, and to generalize conclusions obtained from experimental models. We designed the bioinformatic platform R2 in parallel with a wet-lab approach of neuroblastoma. Here we demonstrate how R2 facilitates an integrated analysis of our neuroblastoma data. Analysis of the MYCN pathway suggested important...

Provenance — who produced it, who reused it

Linked to 23 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.

Standardized, field-standard QC computed by touching the data — every metric states how it was obtained

measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently