The Biocomputing and Biomodelling site serves as Austria’s largest platform for biostatistics and bioinformatics experts in order to develop, share and distribute methods and findings. Questions and research problems can be discussed and solutions will be presented. In addition, the Biocomputing and Biomodelling platform also facilitates the cooperation between life science researchers and biostatisticians/bioinformaticians and can be used for document management and filesharing, for discussions as well as for scheduling of events within the community.

Innovative software solutions will be available  soon in the Biocomputing and Biomodelling app store.

Platomics is an open software platform designed to help researchers to store, analyze and visualize large and complex biological data, such as readouts from Next Generation Sequencers (NGS). The software environment contains powerful features for integrating heterogeneous data and configuring multiple workflow runs, with the ability to "rewind" or access results of intermediate stages. The user can specify the storage and computing locations depending on the nature of the data and the type of analysis being performed; for example, large non-sensitive data sets may be crunched on the public cloud, while human DNA is kept behind an institution’s firewall on local infrastructure. The open nature of the platform means that researchers can easily configure their own workflows and encapsulate software components (e.g. R, Python scripts) as modules that can be re-used in future projects or published on a hosted sharing portal. Then with just a few mouse clicks, other biologists and informaticians can verify results, inspiring them to develop these further and cite the original research. Additionally, Platomics’ standardized APIs enable researchers to integrate modules commissioned from project partners or third-parties, without needing to define complicated software interfaces or specify tool versions. Platomics is offered to the research community to encouraging the sharing of data, algorithms and workflows – and thereby facilitate collaboration and ultimately accelerate scientific progress.