Mathematical models have become an integral part of cancer biology. They are useful tools for deriving a mechanistic understanding of dynamic processes in cancer. The somatic evolutionary process, ...

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their ...

New research has shed light on the complex interactions of stem cell function and molecular diffusion in neural tissue, which may explain many phenomena from stem cell differentiation to the formation ...

Abstract: Early detection and treatment are key components in improving patient survival rates in cases of soft tissue cancers. In this talk, we present a linear elasticity model that describes the ...

Human cancers are thought to be sustained in their growth by a pathologic counterpart of normal adult stem cells: cancer stem cells. This concept was first developed in human myeloid leukemias and is ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Medicine makers need to get better at math. Improved mathematical modeling would accelerate the move toward automated processes, cut production times, and reduce costs. Researchers Francesco Destro, ...

The Covid-19 pandemic has triggered a wave of severe economic disruption around the world, causing widespread chaos, profound changes in the business landscape and overwhelming operational challenges.

"What's the difference between mathematical optimization and machine learning?" This is a question that — as the CEO of a mathematical optimization software company — I get asked all the time.