Robert Gentleman

TL;DR: Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.

TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.

TL;DR: It is shown here that miRNAs are present in human plasma in a remarkably stable form that is protected from endogenous RNase activity and established the measurement of tumor-derived mi RNAs in serum or plasma as an important approach for the blood-based detection of human cancer.

TL;DR: This work describes Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions, including those for sequence analysis, differential expression analysis and visualization.

TL;DR: An overview of Bioconductor, an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology, which comprises 934 interoperable packages contributed by a large, diverse community of scientists.