The value of bioinformatics tools is realized by empowering researchers to make informed decisions based on their data. However, this is not straightforward as every researcher is different, and every data is different, how can we develop tools to effectively meet such needs?

As shown in the figure on the right, we can achieve this in three stages – raw data processing, exploratory data analysis, and prescriptive analytics. For academic research, we are mainly at the first two stage (discovery phase). For translational applications, we need to validate a workflow from exploratory data analysis, and use the established workflow to process future data and decision making (prescriptive analytics). Within such defined workflow and analysis objective, an AI assistant can reason based on the results (together with other contextual information) to drive recommendations for report generation.

In addition to better interfaces and more features compared to the community tools, Pro tools are designed with those goals in mind:

• Efficiency & Productivity - streamlined workflow execution based on templates (i.e. purpose-built workflow) generated from exploratory data analysis, automatic generation of analysis report and slides. The live report permits further refinement toward production grade.
• Stability & Reproducibility - through project management, resumable analysis, and R command tracking
• Better Computing & Support - more computing resources, and prioritized support, and AI co-pilot (coming soon, see below).