DISC Forum

Bio: Kimberly Glass is an expert in complex networks and genomic data analysis. She obtained her PhD in Physics in 2010 from the University of Maryland. From 2010-2014, Dr. Glass was a postdoctoral fellow at Dana-Farber Cancer Institute and the Harvard T.H. Chan School of Public Health where she received training in computational biology. During her post-doc she developed several computational and data-integration methods for inferring and analyzing gene regulatory networks. In 2014 Kimberly joined the faculty of the Channing Division of Network Medicine (CDNM) at Brigham and Women’s Hospital where she is continuing her research in systems medicine and network methods. Her current research focuses on how to integrate and interpret multiple biological data-types in the regulatory network context and on how to understand the biological mechanisms represented in these networks. She is also investigating potential applications of networks in precision medicine, using network approaches to understand susceptibility to, severity, and treatment of complex diseases.

Bio: Phil Chodrow is an applied mathematician who studies networked models of social and biological systems. His methodological interests lie at the intersection of mechanistic modeling and statistical inference. His current work includes graph and hypergraph formation; opinion dynamics on social networks; and gender inequalities in academia. His research has been supported by the NSF Graduate Research Fellowship and the Fulbright Research Scholarship. Phil is an assistant professor in the Department of Computer Science at Middlebury College in Middlebury, Vermont. His teaching specialties at Middlebury include machine learning, network science, and discrete mathematics. Before joining Middlebury, Phil spent two years as a visiting assistant professor in the Department of Mathematics at the University of California, Los Angeles. He received his PhD from the Massachusetts Institute of Technology and his BA from Swarthmore College.

Understanding the complex structure of gene regulation, gene regulatory networks, and how those networks are altered in specific biological contexts, are all critical for developing effective, precision-medicine based therapeutic strategies. Integrating multi-Omics data to model gene regulatory networks can provide unprecedented insights into the mechanisms underlying biological systems. Along these lines, our group has developed a suite of computational approaches that support: (1) effectively integrating multi-Omic data to model gene regulation; (2) performing network analysis to identify regulatory mechanisms mediating changes in biological state; and (3) linking regulatory alterations with patient phenotypes to support precision medicine. In this talk, I will review several specific applications in which we have used these methods to model complex regulatory processes and to gain specific insights into disease.

Well into the 21st century, women remain underrepresented in academic mathematics. In this project, we study the dynamics of female gender representation among the faculty of doctorate-granting mathematics departments. We abstract academic genealogies as a multitype branching process in which advisors generate graduated PhD students, and estimate  the parameters of this process by fitting a mechanistic model of academic careers to a data set derived from the Mathematics Genealogy Project. Upon fitting our model, we find that male academics enjoy an advantage in production of new PhD students relative to their female colleagues, and that this influences the “next generation” due to homophily effects. Our formalism suggests that, without substantial structural shifts, gender representation in most subfields of mathematics will increase slightly before leveling out well short of parity. We close with some reflections on our model’s limitations and what it suggests about interventions to the representation of women in academic mathematics. 

Joint work with Heather Zinn Brooks, Harlin Lee, Anna Haensch, Juan G. Restrepo, and Mason A. Porter.