Literature DB >> 6619661

Parameter estimation techniques for transport equations with application to population dispersal and tissue bulk flow models.

H T Banks, P Kareiva.   

Abstract

We developed techniques for estimating the coefficients, boundary data, and initial data associated with transport equations (or more generally, parabolic distributed models). Our estimation schemes are based on cubic spline approximations, for which convergence results are given. We discuss the performance of these techniques in two investigations of biological interest: (1) transport of labeled sucrose in brain tissue white matter, (2) insect dispersal that cannot be modeled by a random diffusion mechanism alone.

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Year:  1983        PMID: 6619661     DOI: 10.1007/bf00276516

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  3 in total

1.  Random dispersal in theoretical populations.

Authors:  J G SKELLAM
Journal:  Biometrika       Date:  1951-06       Impact factor: 2.445

2.  Gray and white matter brain-blood transfer constants by steady-state tissue clearance in cat.

Authors:  G A Rosenberg; W T Kyner
Journal:  Brain Res       Date:  1980-07-07       Impact factor: 3.252

3.  Bulk flow of brain interstitial fluid under normal and hyperosmolar conditions.

Authors:  G A Rosenberg; W T Kyner; E Estrada
Journal:  Am J Physiol       Date:  1980-01
  3 in total
  4 in total

1.  Revision of the theory of tracer transport and the convolution model of dynamic contrast enhanced magnetic resonance imaging.

Authors:  Stephen L Keeling; Roland Bammer; Rudolf Stollberger
Journal:  J Math Biol       Date:  2007-04-12       Impact factor: 2.259

2.  Measurement and clinical and pharmacokinetic implications of diffusion coefficients of antibiotics in tissues.

Authors:  A Meulemans; F Paycha; P Hannoun; M Vulpillat
Journal:  Antimicrob Agents Chemother       Date:  1989-08       Impact factor: 5.191

3.  Parameter estimation techniques for interaction and redistribution models: a predator-prey example.

Authors:  H T Banks; P M Kareiva; K A Murphy
Journal:  Oecologia       Date:  1987-12       Impact factor: 3.225

4.  Analyzing collective motion with machine learning and topology.

Authors:  Dhananjay Bhaskar; Angelika Manhart; Jesse Milzman; John T Nardini; Kathleen M Storey; Chad M Topaz; Lori Ziegelmeier
Journal:  Chaos       Date:  2019-12       Impact factor: 3.741

  4 in total

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