The fully automated demonstrated in is a particularly advanced example of a system for quantitative phenotypic analysis that integrates all steps of the scientific process, from hypothesis creation, through testing the hypothesis and results interpretation to the planning of further experimental steps based on the obtained results. While being an impressive tool for next generation high-throughput experiments, such a system is still expensive and not suitable for the relatively small batch sizes and constantly changing protocols encountered in the daily work of characterizing biological entities and developing new methods. In this work, we describe a framework that was designed to bride the gap between advanced high-throughput systems and manual bench work. It integrates automated protocol execution with computer-based data interpretation to allow reactions to measurement outcomes in autonomous experiments, but at the same time it has been designed to make it as easy as possible to use it for different types of experiments without extensive Valrubicin reprogramming. Our system is unique by the fact that it is based on abstract, object oriented descriptions of experiments written in the R programming language that provides a wide range of statistical tools for experimental planning and data-analysis. It allows to carry-out experiments by specifying only abstract protocol parameters such as component names, concentrations and incubation times. The necessary calculations for translating this information into Ticarcillin disodium volumes, pipetting patterns and commands that can be executed by a robot are done automatically, greatly reducing the effort for setting up new experiments and providing a very convenient interface to computer-based experiment planning. We implemented a variety of tools for generating experimental designs, optimizing experimental procedures and for analyzing, visualizing and interpreting experimental data. All of them interact seamlessly with the automation framework, avoiding unnecessary data-conversions and allowing their use in autonomous experiments.