Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer.

By Daniel R. Rhodes, T. Barrette, Mark A. Rubin, Debashis Ghosh, Arul M. Chinnaiyan. Cancer Research, 2002

703 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0eaa28aa3612057f8af7c93c59e03f26e3f67ca8

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Citations in the corpus

Comprehensive literature review and statistical considerations for microarray meta-analysis (2012, methodology): “For all the ﬁve methods, statistical inference can be performed parametrically under the assumption that P -values are uniformly distributed under the null hypothesis or can be done non-parametrically by permutation-based analysis (109,112).”
Coexpression analysis of human genes across many microarray data sets. (2004, background): “genes that distinguish different sets of samples (Breitling et al. 2002; Rhodes et al. 2002; Yuen et al. 2002; Choi et al. 2003; Detours et al. 2003; Ramaswamy et al. 2003; Sorlie et al. 2003; Xin et al. 2003).”
Androgen-Independent Prostate Cancer Is a Heterogeneous Group of Diseases (2004, background): “(6, 7, 40) This initial work grouped all of the Fig.”
Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach (2015, background): “…The Cancer Genome Atlas (TCGA) pilot projpro.les and clinical symptoms, we can have a better view ect has made tremendous efforts and generated a large on the pathogenic mechanisms of cancer diseases, and amount of cross-platform genomic data for exploring the complex landscapes of human…”
Combining multiple microarray studies and modeling interstudy variation (2003, methodology): “As an illustration, we examined the purine biosynthesis pathway that had been provided as biological evidence in Rhodes et al. (2002).”
PAGE: Parametric Analysis of Gene Set Enrichment (2005, unknown): “Each approach was shown to lead to better congruency among diverse data sets than would be achieved by direct comparison of data sets, whether in demonstrating common transcriptional profiles of prostate cancer [34], common molecular markers of lung cancer [15], or a common biological theme in diabe”