Bioconductor Project Working Papers
About the Bioconductor Project Working Papers
The Bioconductor Project is an open source and open development software project for the analysis and comprehension of biomedical and genomic data. Core developers are located at research institutions worldwide. The broad goals of the Bioconductor Project include
- providing access to a wide range of powerful statistical and graphical methods for the analysis of genomic data;
- facilitating the integration of biological metadata in the analysis of experimental data (e.g., literature data from PubMed, annotation data from GO and LocusLink);
- allowing the rapid development of extensible, scalable, and interoperable software;
- promoting high-quality documentation and reproducible research;
- providing training in computational and statistical methods for the analysis of genomic data.
R and the R package system are the main vehicles for designing and releasing software. R is a widely-used open-source language and environment for statistical computing and graphics -- GNU's S-Plus. It provides a high-level programming environment, together with a sophisticated packaging and testing paradigm. It has a number of mechanisms that allow it to interact directly with software that has been written in different languages and environments (Omega Project).
Scope of the Bioconductor Project Working Papers Series
The purpose of this series is to collect and disseminate articles on statistical methods and software for the analysis and comprehension of biomedical and genomic data. The series focuses in particular on articles related to the Bioconductor Project and written by either Bioconductor core developers or contributors. Contributions within the scope of the series include
- research advances in statistical computing;
- research advances in statistical design and analysis methods;
- research advances in bioinformatics;
- research advances in computational biology;
- innovative applications of statistical and computational methods to biomedical and genomic data;
- review articles, perspectives, and notes on topics that might be of interest to users and developers of Bioconductor software.
Please follow the Authors Instructions for submission guidelines.