One can point to a variety of historical milestones for gender equality in STEM (science, technology, engineering, and mathematics), however, the practical effects are gradual and ongoing. It is important to quantify gender differences in subdomains of scientific work in order to detect potential biases and to monitor progress. In this work, we studied the relevance of gender in scientific collaboration patterns in the Institute for Operations Research and the Management Sciences (INFORMS), a professional organization with sixteen peer-reviewed journals. We constructed a large temporal bipartite network between authors and publications, using the organization's publication data from 1952 to 2016, and augmented the author nodes with gender labels. We characterized differences in several basic statistics of this network over time, highlighting how they change with respect to relevant historical events. We found a steady increase in participation by women (e.g., fraction of authorships by women and of new women authors) starting ∼1980. However, women still comprise less than 25% of the INFORMS society, and are additionally underrepresented among authors with many publications. Finally, we describe a methodology for quantifying differences in the role that authorships by women and men play in the overall connectivity of the network. Specifically, we propose a degree-preserving temporal and geometric null model with emergent communities. We use two measures of edge importance related to diffusion throughout the network, namely effective resistance and edge contraction importance to quantify gender differences in collaboration patterns that go beyond differences in local statistics.