Popper and the Omics

and other-omics generate unprecedented amounts of experimental data about cells or tissues under certain conditions. However, from an epistemological point of view, merely fitting data into a model to explain observations is not sufficient; science should strive to describe simple and logical theoretical systems that are testable and that enable predictions (Popper, 1959). This paper tries to alleviate this dilemma by suggesting data mining strategies to support the conversion of Omics data into resilient models. Inductive science, which draws conclusions from empirical observations, is descriptive, and multiple models can explain the same set of data. The prediction of future events from past observations might be plausible and could appear to be in agreement with our experiences, but the derivation of natural laws or theories cannot be justified by fitting observations into a model. This " problem of induction " was introduced by Hume in the eighteenth century (Hume, 1748) and is generally accepted in epistemology. Popper illustrates this fundamental problem in the theory of knowledge creation with his famous example of white and black swans: " Now it is far from obvious, from a logical point of view, that we are justified in inferring universal statements from singular ones, no matter how numerous; for any conclusion drawn in this way may always turn out to be false: no matter how many instances of white swans we may have observed, this does not justify the conclusion that all swans are white " (Popper, 1959). In contrast, deductive science begins with a hypothesis or theory and proceeds to derive possible conclusions and statements that are testable, either logically or experimentally. Since it might be impossible to verify truth, even assuming infinite data, Karl Popper suggested the concept of falsifiability (Popper, 1959): Instead of collecting evidence in support of a certain hypothesis, the borders of the validity of a hypothesis are systematically explored by testing its possible theoretical consequences. This strategy is known as " The Scientific Method. " The starting point for formulating a scientific hypothesis is usually an idea that gives a fresh and surprising view on reality. Whereas the evaluation of a new theory is a strictly systematic process, the generation of a hypothesis depends on the creativity and intuition of the researcher. However, Omics projects usually start with a biological question or a medical problem (see Figure 1). For example, one may wish to investigate the physiological changes of …