Krohs Ulrich
Department of Philosophy, University of Bielefeld, Universitätsstr. 25, 33615 Bielefeld, Germany.
Stud Hist Philos Biol Biomed Sci. 2012 Mar;43(1):52-7. doi: 10.1016/j.shpsc.2011.10.005. Epub 2011 Oct 28.
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.
系统生物学旨在通过分子网络的详细模型来解释生命过程，主要是在全细胞尺度上。全细胞视角将系统生物学这一新领域与分子细胞生物学中的早期方法区分开来。这种转变之所以成为可能，是因为为收集“组学”（基因组学、蛋白质组学等）数据而开发的高通量方法。这些新技术作为半自动分析设备、现成的分析试剂盒和探针阵列在商业上可用。对于所谓的便捷实验，有一整个供应行业。我的论文探讨了系统生物学中严重依赖便捷实验的一些认知后果。在实验自动化程度较低的时代，建模以及部分实验甚至可以被很好地理解为要么由假设驱动，从而通过假设检验来进行，要么以探索模式进行，旨在明确概念或最初模糊的现象。在系统生物学中，情况截然不同。数据收集变得如此容易（尽管不便宜），以至于实验在很大程度上由便捷设备驱动，而模型构建则由便捷实验产生的大量数据驱动。这导致了科学模式的转变。论文表明，便捷驱动的科学既不是主要的假设检验，也不是处于探索模式。它更像是以收集模式进行。这种转变要求评估模式进行另一种转变，鉴于收集到的数据过多，评估现在变成了一种探索性的努力。
