Bioconductor Conference: Expanding Training, Mentorship, and Collaboration in Genomic Data Science - Bioconductor is one of the most widely used open-source platforms in biomedical data science. Its rigorously reviewed ecosystem of more than two thousand interoperable software, annotation, and data packages supports analyses in single-cell and spatial transcriptomics, bulk RNA-seq, epigenomics, proteomics, microbiome research, metabolomics, and image-based assays. Bioconductor tools appear in more than ninety thousand publications and form a core component of the computational infrastructure through which NIH-funded investigators develop, disseminate, and apply reproducible analytical methods across a broad range of technologies and diseases. Since 2001, the Bioconductor Conference (BioC) has served as the primary venue for scientific exchange, developer training, and community building. The meeting provides introductory workshops for new users, hands-on workshops for applied researchers, and collaboration opportunities for method developers whose software underpins modern genomics. Despite its impact, the conference is entirely self-funded. However, due to the rapid expansion of the user community, by necessity the focus of the original meeting has shifted qualitatively towards new user engagement and introductory instruction. This has proportionally reduced capacity for covering relatively advanced topics such as structured developer mentoring, high-quality instructional material development, or in-person scientific exchange around emerging technologies that require coordinated methodological innovation. Hence, this R13 proposal seeks to expand the scope of BioC so that it can serve the full community spectrum from experienced developers to new users more effectively and sustainably. Dedicated support will strengthen collaboration among scientists developing new analytical approaches, enhance mentoring and professional development for early-career researchers, and broaden participation by providing travel and registration assistance for trainees and investigators from under-resourced institutions. Funding will also support the development and dissemination of pedagogically robust, openly available workshop materials that promote reproducible analysis across rapidly evolving data types. By integrating methodological innovation, open-source software development, hands-on training, and community engagement, the Bioconductor Conference advances NHGRI and ODSS priorities in rigorous and reproducible research, open science, workforce development, data standards, and cloud-enabled biomedical computation. Expanded support will ensure that the conference continues to accelerate the translation of statistical methods into reliable tools and sustains the skilled, diverse developer community required for the next generation of genomic and multi-scale biomedical research.
