Genomics: BxGenomics Bulk RNA-Seq View Just Got a Major Upgrade — Here's What's New
| BioInfoRx is excited to announce a major update to the BxGenomics Bulk RNA-Seq View database, bringing a substantially larger collection of public RNA-Seq datasets to researchers and reinforcing BxGenomics' position as one of the most comprehensive online platforms for human and mouse transcriptomics data mining. |  |
The updated database now houses more than 56,400 projects and 1.82 million samples drawn from publicly available human and mouse RNA-Seq studies, representing a near doubling of the platform's previous capacity. With over 31,000 projects and over 890,000 samples newly incorporated, this release marks one of the largest single additions to the BxGenomics repository to date.
A key focus of this release was bringing the platform up to date with the latest published research. RNA-Seq output has accelerated sharply over the past several years, and the updated BxGenomics database now keeps pace — capturing studies published through 2025 and integrating thousands of datasets from 2022 onward that were previously absent from the platform. Researchers no longer need to hunt through external repositories to find recent data; it is now readily accessible within the BxGenomics environment.
The update also signals a broader reach across the scientific publishing landscape. The number of journals represented in the database has grown from 770 to 1,285, spanning fields such as cancer biology, immunology, developmental biology, neuroscience, and metabolism. From flagship journals like Nature, Cell, and Science to specialized titles such as Blood, Oncogene, and Genes & Development, the expanded collection reflects the breadth and richness of modern RNA-Seq research.
For researchers, the practical implication is straightforward: more data, more context, and more opportunity for discovery. The BxGenomics platform allows users to search, filter, and analyze datasets without any coding experience, feeding results directly into QuickOmics for downstream visualization and pathway analysis. Teams looking to contextualize their own findings against the published literature now have a substantially richer resource at their fingertips.
Read the full blog post → Explore Bulk RNA-Seq View →
