The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics (CBB). The project aims to foster collaborative development, reduce barriers to entry into interdisciplinary scientific research, and promote the achievement of remote reproducibility of research results. Key features of the project include transparency, reproducibility, and efficiency of development. The software development strategy is based on modular design, object-oriented programming, and automated resource distribution. The project emphasizes the use of the R programming language, which offers prototyping capabilities, packaging protocols, object-oriented programming support, WWW connectivity, statistical simulation and modeling support, and visualization support. The Bioconductor project also focuses on distributed development, reuse of exogenous resources, and publication and licensing of code under an open-source license. The project addresses specific challenges in CBB, such as reproducibility, data evolution and complexity, training users, and responding to user needs. The infrastructure in R and Bioconductor supports reproducible and replayable research, and the project provides comprehensive documentation and training materials to facilitate user adoption and development.The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics (CBB). The project aims to foster collaborative development, reduce barriers to entry into interdisciplinary scientific research, and promote the achievement of remote reproducibility of research results. Key features of the project include transparency, reproducibility, and efficiency of development. The software development strategy is based on modular design, object-oriented programming, and automated resource distribution. The project emphasizes the use of the R programming language, which offers prototyping capabilities, packaging protocols, object-oriented programming support, WWW connectivity, statistical simulation and modeling support, and visualization support. The Bioconductor project also focuses on distributed development, reuse of exogenous resources, and publication and licensing of code under an open-source license. The project addresses specific challenges in CBB, such as reproducibility, data evolution and complexity, training users, and responding to user needs. The infrastructure in R and Bioconductor supports reproducible and replayable research, and the project provides comprehensive documentation and training materials to facilitate user adoption and development.