Convenience experimentation.
Systems biology aims at explaining life processes by means of detailed models of molecular networks, mainly on the whole-cell scale. The whole cell perspective distinguishes the new field of systems biology from earlier approaches within molecular cell biology. The shift was made possible by the high throughput methods that were developed for gathering 'omic' (genomic, proteomic, etc.) data. These new techniques are made commercially available as semi-automatic analytic equipment, ready-made analytic kits and probe arrays. There is a whole industry of supplies for what may be called convenience experimentation. My paper inquires some epistemic consequences of strong reliance on convenience experimentation in systems biology. In times when experimentation was automated to a lesser degree, modeling and in part even experimentation could be understood fairly well as either being driven by hypotheses, and thus proceed by the testing of hypothesis, or as being performed in an exploratory mode, intended to sharpen concepts or initially vague phenomena. In systems biology, the situation is dramatically different. Data collection became so easy (though not cheap) that experimentation is, to a high degree, driven by convenience equipment, and model building is driven by the vast amount of data that is produced by convenience experimentation. This results in a shift in the mode of science. The paper shows that convenience driven science is not primarily hypothesis-testing, nor is it in an exploratory mode. It rather proceeds in a gathering mode. This shift demands another shift in the mode of evaluation, which now becomes an exploratory endeavor, in response to the superabundance of gathered data.
Department of Philosophy, University of Bielefeld, Universitätsstr. 25, 33615 Bielefeld, Germany. ulrich.krohs@uni-bielefeld.de
Ulrich
U
Krohs
D001331:Automation; D019295:Computational Biology; D003625:Data Collection; D023281:Genomics; D008954:Models, Biological; D008967:Molecular Biology; D040901:Proteomics; D012107:Research Design; D049490:Systems Biology