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Using agent-based modeling as “virtual laboratory”

RRB 736

Agent-based models simulate individual cells as software objects, each with their own independent states and behavioral “rules” that codify our biological hypotheses. Generally, they also are tied to models of the chemical microenvironment to emulate the motion of oxygen, growth and signaling factors, and therapeutic compounds. Together, these can form a “virtual laboratory” to computational […]

More than genetics: the role of the ecosystem in cancer evolution and treatment resistance

Light Hall 415ABCD

Somatic evolution is increasingly being recognized as the main driver not only in cancer progression but importantly in the emergence of resistance to existing treatments. Much of the focus in the research of evolution in cancer has been devoted to leveraging existing -omics tools to evaluate how tumors change but Darwinian evolution requires us to […]

Modeling Subcellular Mass Distributions with Optimal Transport: Applications in Cancer

Bass Conference Room - RRB 436

Microscopic imaging techniques have given us access to high fidelity measurements of subcellular molecule and protein mass distributions. Quantitative analysis of these has the potential to elucidate biological mechanisms as well help perform diagnosis and clinical outcome predictions in cancer and other pathologies. By using the mathematics of optimal transport we can quantitatively compare distributions […]