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The Geddes Composable Platform is an on-premise Kubernetes-based private cloud at Purdue University and was designed to meet the increased demand for the deployment of flexible, persistent, edge and supporting services for scientific data analysis and to promote "SciOps", the application of DevOps principles to scientific computing. The platform has been in an early user access period for the past six months and has been used by several research groups at Purdue and by students as part of data science initiatives on campus. In this lightning talk, we will give a brief overview of the platform and its components, summarize the usage during the early user access period and describe scientific research and education use cases that have been enabled by the Geddes platform. At the time of writing, over sixty users from fifteen research groups have been given access to the platform. Deployments include JupyterHub instances for specific research groups and data science courses, science gateways, databases, ML-based image classifiers, and web-based BLAST database searches.

We have developed the Proteome Discovery Pipeline, a stand-alone bioinformatics platform used for LC/MS data analysis and biomarker discovery. Data is processed in a series of self-contained analytical steps using modules that are controlled by a graphical user interface. The user interface was developed in Visual C++ 6.0 and provides a multi-threaded, tabbed user interface with each tab representing a step in the analysis process. Modules included are spectrum deconvolution, alignment, normalization, significance tests and pattern recognition. Modules consist of applications developed in C++ and the R scripting language, which are called as external processes from the GUI using inputted parameters. Molecular correlation analysis can be viewed interactively using SysNet. Figure 1 shows the architecture of the Proteome Discovery Pipeline.