 Systems biology and synthetic biology are relatively recent interdisciplinary approaches that aim to improve our ability to understand, predict, and control living systems. They both capitalize on large-scale data production in genomics and related fields and explore new paths of cross-fertilization between biology and non-biological disciplines such as physics, computer science, mathematics, chemistry, and engineering. Systems and synthetic biology are often described as ‘sister-disciplines’ or ‘cousins’, focusing on the complementary and interrelated aims of understanding (systems biology) and designing (synthetic biology) living systems. Accordingly, they have been associated with knowledge-driven versus application-driven epistemologies, or with the aims of analysis versus synthesis. Philosophers of science examining the research practice have, however, argued that understanding and design are often interdependent, and that no simple distinction between basic and applied science can be made in this context (Kastenhofer 2013a,b; Knuuttila &amp; Loettgers 2013a; O’Malley 2009). Moreover, the notions of systems and synthetic biology cover broad and highly diverse spectra of interdisciplinary hybrids (Calvert &amp; Fujimura 2011; Gramelsberger et al. 2013). This entry will therefore aim to reach a balance between displaying the methodological flexibility and variability within these fields and highlighting common themes.