Nathaniel Linden

Ph.D. Student

I am currently a Ph.D. student in the Department of Mechanical and Aerospace Engineering and the Interfaces Graduate Training Programming at University of California San Diego, where I work in the labs of Boris Kramer and Padmini Rangamani. My research focuses on developing data-driven modeling and uncertainty quantification methods for systems biology. Specifically, I am interested in improving how we use experimental data to calibrate and inform mathematical models of intracellular signaling systems. To learn more about my current research, please visit the Projects page.

In 2020, I received my BS of Bioengineering with a minor in Applied Mathematics from the University of Washington in Seattle. At UW, I worked with Bing Brunton to develop a novel method to visualize spatiotemporal structures in widefield optical recordings of neural calcium activity.

News

Mar 28 2023 I will be giving a talk on my new research on multimodel modeling for clinical applications at the SOCAMS 2023 at UC Irvine in April.
Jan 15 2023 I presented a poster on my work on Bayesian inference for systems biology at the Biophysical Society 2023 Annual Meeting.
Oct 25 2022 My paper titled “Bayesian Parameter Estimation for Dynamical Models in Systems Biology” was published is PLoS Computational Biology and is available here.
Sep 30 2022 I co-organized a minisymposium on Parameter Inference and Uncertainty Quantification for Systems Biology and Medicine at the SIAM Conference on Mathematics of Data Science in San Diego, CA. Additionally, I presented my work on Bayesian parameter estimation and uncertainty quantification for systems biology.
May 21 2022 I presented my work on Bayesian parameter estimation in systems biology at the Southern California Applied Mathematics Symposium 2022 at Harvey Mudd College in Claremont, CA in May, 2022.
Apr 15 2022 I presented my work on Bayesian parameter estimation in systems biology at the 2022 SIAM Conference on Uncertainty Quantification in Atlanta, GA on April 12 - 15, 2022. My presentation was included in the minisymposium on Efficient Uncertainty Quantification with Physics-Informed and Data-Driven Models.
Apr 11 2022 My paper titled “Bayesian Parameter Estimation for Dynamical Models in Systems Biology” is available as a preprint here.
Sep 10 2021 I was accepted to join the UCSD Interfaces Training Program in Multi-scale Biology and was awarded funding through an NIH training grant.
Aug 25 2021 My paper, Go with the FLOW: visualizing spatiotemporal dynamics in optical widefield calcium imaging, with Bing Brunton, Steve Brunton, Nick Steinmetz, Bill Moody and Dennis Tabuena was published in the Journal of the Royal Society Interface.
Jul 30 2021 I was featured on the UCSD Jacobs School of Engineering blog!

Selected Publications

  1. SIAM News
    Identifiability and Sensitivity Analysis for Bayesian Parameter Estimation in Systems Biology
    Linden, Nathaniel J., Rangamani, Padmini, and Kramer, Boris
    SIAM News 2023
  2. PLoS Comput. Biol
    Bayesian parameter estimation for dynamical models in systems biology
    Linden, Nathaniel J., Kramer, Boris, and Rangamani, Padmini
    PLOS Computational Biology 2022