Experts in the field of molecular and cellular biology (MCB) use domain-specific reasoning strategies to navigate the unique complexities of the phenomena they study and creatively explore problems in their fields. One primary goal of instruction in undergraduate MCB is to foster the development of these domain-specific reasoning strategies among students. However, decades of evidence-based research and many national calls for undergraduate instructional reform have demonstrated that teaching and learning complex fields like MCB is difficult for instructors and learners alike. Therefore, how do students develop rich understandings of biological mechanisms? It is the aim of this dissertation work to explore features of expertise and knowledge building in undergraduate MCB by investigating knowledge organization and problem-solving strategies. Semi-structured clinical think-aloud interviews were conducted with introductory and upper-division students in MCB. Results suggest that students must sort ideas about molecular mechanism into appropriate mental categories, create connections using function-driven and mechanistic rather than associative reasoning, and create nested and overlapping ideas in order to build a nuanced network of biological ideas. Additionally, I characterize the observable components of generative multi-level mechanistic reasoning among undergraduate MCB students constructing explanations about in two novel problem-solving contexts. Results indicate that like MCB experts, students are functionally subdividing the overarching mechanism into functional modules, hypothesizing and instantiating plausible schema, and even flexibly consider the impact of mutations across ontological and biophysical levels. However "filling in" these more abstract schema with molecular mechanisms remains problematic for many students, with students instead employing a range of developing mechanistic strategies. Through this investigation of expertise and knowledge building, I characterize several of the ways in which knowledge integration and generative explanation building are productively constrained by domain-specific features, expand on several discovered barriers to productive knowledge organization and mechanistic explanation building, and suggest instructional implications for undergraduate learning.