R. Gentleman

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The basic characteristics of the GO (The Gene Ontology Consortium, 2000) data are described in ? and the interested reader is referred there for more details. In this paper we assume that readers are familiar with the basic DAG structure of GO and with the mappings of genes to GO terms that are provide by GOA (Camon et al., 2004). We examine some of the(More)
In this paper a new approach to local likelihood estimation for censored data is proposed. This method employs the full likelihood and alternates between estimating the baseline hazard and estimating the covariate effect. The proposed methodology incorporates multidimensional data via additive models. Some results regarding inference for the covariate(More)
In this paper methods for nding the non{parametric maximum likelihood estimate (NPMLE) of the distribution function of time to event data will be presented. The basic approach is to use graph theory (in particular intersection graphs) to simplify the problem. Censored data can be represented in terms of their intersection graph. Existing combinato-rial(More)
flowUtils-package Utilities for flow cytometry data Description This package includes functions to import Gates,transformations and compensations defined in compliance with Gating-ML Candidate recommendation for Gating Description.(Version V 1.5) This package depends on the flowCore package for methods to evaluate the gatingML files read into the workspace.(More)
In Ge et al. (2001) the authors consider an interesting question. They assemble gene expression data from a yeast cell-cycle experiment (Cho et al., 1998), literature proteinprotein interaction (PPI) data and yeast two-hybrid data. We have curated the data slightly to make it simpler to carry out the analyses reported in Ge et al. (2001). In particular we(More)
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