 Mechanistic accounts initially emphasized the differences between the explanatory ideal of covering laws in physics and explanations in molecular biology (Craver &amp; Tabery 2015). Mechanistic explanations cite how biological functions arise from the interactions and organization of component parts or entities (Bechtel &amp; Richardson 1993; Machamer et al. 2000; Glennan 2002). Since research in systems biology is often integrated with research in molecular and cell biology, some have argued that many cases in systems biology can readily be seen as an extension of mechanistic research (Boogerd et al. 2013; Richardson &amp; Stephan 2007). But although abstract modeling is compatible with mechanistic research, it is a contested issue whether abstract models are developed towards research aims that are distinct from mechanistic explanations. While some contend that mathematical models are primarily used as inputs to or heuristics for mechanistic explanations, i.e., as mechanistic schemas (Darden 2002; Matthiessen 2015), others interpret the emphasis on quantitative and dynamic aspects as a departure from mechanistic explanations. One argument in support of the latter is that the modeling process does not proceed from abstract to more detailed models, but in the opposite direction, suggesting that mechanistic details may be vehicles for more generic explanations rather than the other way around (Braillard 2010; Serban &amp; Green 2020). A second argument refers to the difficulty of reconstructing a causal story from the abstract mathematical models (Issad &amp; Malaterre 2015). Systems biology may therefore also offer cases of non-mechanistic explanations.