Multiscale Modeling/Inverse Problems: Forward and Inverse Methods for Stochastic Models of Diffusing Particles in Complex Biofluids
Abstract
The objective of this grant has been to improve the scientific communitys understanding of experiments tracking individual particles in biofluids. The experiments consist of tracking and recording tracer particles propelled by the thermal motion of molecules in complex biofluids such as cytoplasm or lung mucus. The investigation is inherently nanometric in scale and thus rather delicate, and the recorded data displays manifold evidence of anomalous (non-Brownian) particle dynamics. Nevertheless, most analyses to date have relied on variations of the traditional method of moments (based on the sample mean, sample variance, etc.), and have often lacked any support from sound statistical methodology such as asymptotic theory. The work funded by this grant has built more robust methodology through maximum likelihood and spectral (wavelet) estimation, and has contributed to a new perception of the relation between stochastic and mechanistic models. By linking the data to particular models, the investigators have been developing statistical tests for which biological mechanisms are linked to particular aspects of the stochastic dynamics of tracer particles.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2018
- Accession Number
- AD1070628
Entities
People
- John Fricks
Organizations
- Pennsylvania State University