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Robert Gentleman
Researcher at Genentech
Publications - 140
Citations - 53506
Robert Gentleman is an academic researcher from Genentech. The author has contributed to research in topics: Bioconductor & Gene expression profiling. The author has an hindex of 52, co-authored 139 publications receiving 48510 citations. Previous affiliations of Robert Gentleman include Harvard University & Brigham and Women's Hospital.
Papers
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Querying genomic databases: refining the connectivity map.
TL;DR: Two key aspects of the Connectivity Map implementation are revisited, including new approaches to measuring closeness for the common scenario wherein the query constitutes an ordered list and an alternate inferential approach based on generating empirical null distributions that exploit the scope, and capture dependencies, embodied by the database.
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Top-down standards will not serve systems biology.
John Quackenbush,Christian J. Stoeckert,Catherine A. Ball,Alvis Brazma,Robert Gentleman,Wolfgang Huber,Rafael A. Irizarry,Marc L. Salit,Gavin Sherlock,Paul T. Spellman,Neil Winegarden +10 more
TL;DR: The proposed solution to the development of standards in systems-biology research is presented as a ‘top-down’ approach that ignores many existing and emerging standards and seems based on false assumptions about the research community and ignores the community it is intended to serve.
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Bayesian Error‐in‐Variable Survival Model for the Analysis of GeneChip Arrays
TL;DR: A Bayesian error‐in‐variable model is described for the analysis of microarray data from a clinical study of patients with acute lymphoblastic leukemia, focusing in particular on the problem of identifying genes whose expression patterns are associated with duration of remission.
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Reply to Talloen et al.: Independent filtering is a generic approach that needs domain specific adaptation
TL;DR: In the example reported by Talloen et al. (1), the detection power achieved by the more general—and thus, more broadly applicable—overall variance filter was as good as or better than that of a technology-specific criterion at all filtering thresholds.
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Wavelet thresholding with bayesian false discovery rate control.
TL;DR: This article proposes controlling the positive FDR using a Bayesian approach where the rejection rule is based on the posterior probabilities of the null hypotheses, and illustrates the procedure with an application to wavelet thresholding.