Aeskulap is a medical image viewer. It is able to load a series of special images stored in the DICOM format for review. It is able to query and fetch DICOM images from archive nodes (also called PACS) over the network. The goal of this project is to create a full open source replacement for commercially available DICOM viewers. It is based on gtkmm, glademm, and gconfmm and designed to run under Linux. Ports of these packages are available for different platforms. It should be quite easy to port It to any platform were these packages are available.
BioCoRE is a collaborative work environment for biomedical research, research management, and training. It features easy-to-use tools, among them co-authoring papers and other documents, running applications on supercomputers, sharing molecular visualization over the Internet, notifying project team members of recent project changes by email, chatting, keeping a lab book, and other practical features.
Bioconductor is a set of packages for R (a GPLd statistical data analysis language) which focus on bioinformatics data analysis, especially gene expression arrays (Affymetrix, cDNA spotted arrays). There are tools for statistical normalization, differential expression, genomic visualization, and biological annotation. Future work includes implementation and development of better statistical methods, distributed computing, visualization, and extensions to related high-throughput laboratory assays. The primary developers are research statisticians.
Blossoc is a linkage disequilibrium association mapping tool that attempts to build (perfect) genealogies for each site in the input, score these according to non-random clustering of affected individuals, and judge high-scoring areas as likely candidates for containing disease affecting variation. Building the local genealogy trees is based on a number of heuristics that are not guaranteed to build true trees, but have the advantage over more sophisticated methods of being extremely fast. Blossoc can therefore handle much larger data sets than more sophisticated tools, but at the cost of sacrificing some accuracy.