Abstract
Biological systems are complex and highly interconnected. Despite increasing amounts of information collected, it is not always clear how to use these data to make conclusions and predictions. Mathematical models are powerful tools in biology because they allow us to abstract the biological system in order to frame questions, explore patterns and synthesize information. Indeed, we are writing these remarks during the COVID-19 Pandemic which has illustrated in a staggering way the importance of quantitative modeling in aiding our understanding of complex biological processes. This volume contains the scientific and collaborative work from the Collaborative Workshop for Women in Mathematical Biology. The workshop brought together forty-five researchers to collaborate on seven problems each of which used mathematics to understand complex biological systems. The workshop was held at the Institute of Pure and Applied Mathematics on the campus of University of California, Los Angeles from June 17-21, 2019 in Los Angeles, CA and was organized by Rebecca Segal, Blerta Shtylla, and Suzanne Sindi. The articles contained in this volume were initiated during the intensive one-week workshop and continued through follow-up collaborations afterwards.
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Acknowledgements
The work described herein was initiated during the Collaborative Workshop for Women in Mathematical Biology hosted by the Institute for Pure and Applied Mathematics at the University of California, Los Angeles in June 2019. Funding for the workshop was provided by IPAM, the Association for Women in Mathematics’ NSF ADVANCE “Career Advancement for Women Through Research-Focused Networks” (NSF-HRD 1500481) and the Society for Industrial and Applied Mathematics.
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Segal, R., Shtylla, B., Sindi, S. (2021). Collaborative Workshop for Women in Mathematical Biology. In: Segal, R., Shtylla, B., Sindi, S. (eds) Using Mathematics to Understand Biological Complexity. Association for Women in Mathematics Series, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-57129-0_1
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DOI: https://doi.org/10.1007/978-3-030-57129-0_1
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