Living systems have paradoxical thermodynamic stability, the intrinsic property of self-organization, fluctuation and adaptation to their changing environment. Knowledge accumulated in the analytical reductionist framework has provided useful systematic descriptions of biological systems which appear to be insufficient to gain deep understanding of their behaviour in physiologic conditions and diseases. A state-of-the-art functional genomics study in yeast points to the current inability to appraise 'biological noise', leading to focus on few genes, transcripts and proteins subject to major detectable changes, while currently inaccessible small fluctuations may be major determinants of the behaviour of biological systems. We conjecture that biological systems self-organize because they operate as a conjunction between the relatively variable part of a stable organization and the relatively stable part of a chaotic network of fluctuations, and in a space with a changing number of dimensions: biological space-time. We propose to complement the precepts of the analytical reductionist framework with those of the biosystemic paradigm, in order to explore these conjectures for systems biology, combining in an iterative mode systemic modelling of biological systems, to generate hypotheses, with a high level of standardization of high-throughput experimental platforms, enabling detection of small changes of low-intensity signals, to test them.