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Automating Science and Finding Patterns in the Data

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Automating Science and Finding Patterns in the Data

Ross D. King

Department of Computer Science, University of Wales, Aberystwyth, SY23 3DB, UK rdk@aber.ac.uk

Abstract. The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable repro- ducibility. We report the development of the Robot Scientist ”Adam”

which advances the automation of both. Adam has autonomously gen- erated functional genomics hypotheses about the yeast Saccharomyces cerevisiae, and experimentally tested these hypotheses using laboratory automation. We have confirmed Adam’s conclusions through manual ex- periments. To describe Adam’s research we have developed an ontology and logical language. The resulting formalization involves over 10,000 dif- ferent research units in a nested tree-like structure, ten levels deep, that relates the 6.6 million biomass measurements to their logical descrip- tion. This formalization describes how a machine discovered new scien- tific knowledge. Describing scientific investigations in this way opens up new opportunities to apply data-mining to discover new knowledge. To test this idea we have applied relational data-mining, guided by ontology, to evaluate the repeatability of Adam’s investigations.

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