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Difference between revisions of "Dynamic Multi-System Resilience in Human Aging/LuisAmaral"

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Ingrid's talk has raised many interesting questions about the different types of models and their different purposes.  My thought is that we need research occurring at all types of models with the understanding that  each type can contribute to the others. For example, the parametrized, complex climate/ecological models enable us to conduct computational experiments that otherwise would be impossible.  However, because of the complexity of the model it is impossible to gain insight on which specific experiments to conduct.  Simpler, stylized models, that could be developed and tested against the complex models, could provide the insight to select what computational experiments to conduct.
 
Ingrid's talk has raised many interesting questions about the different types of models and their different purposes.  My thought is that we need research occurring at all types of models with the understanding that  each type can contribute to the others. For example, the parametrized, complex climate/ecological models enable us to conduct computational experiments that otherwise would be impossible.  However, because of the complexity of the model it is impossible to gain insight on which specific experiments to conduct.  Simpler, stylized models, that could be developed and tested against the complex models, could provide the insight to select what computational experiments to conduct.
|Reference material notes=[https://amaral.northwestern.edu/people/amaral/fractal-dynamics-in-physiology-alterations-with-disease-and-aging Fractal dynamics in physiology: Alterations with disease and aging]
 
 
Goldberger AL, Amaral LAN, Hausdorff JM, Ivanov PC, Peng CK, Stanley HE
 
 
''Proc. Natl. Acad. Sci. U. S. A.'' 99, 2466-2472 (2002)
 
 
[https://amaral.northwestern.edu/people/amaral/physiobank-physiotoolkit-and-physionet-components-of-a-new-research-resource-for-complex-physiologic-signals PhysioBank, PhysioToolkit, and PhysioNet - Components of a new research resource for complex physiologic signals]
 
 
Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE
 
 
''Circulation'' 101, E215-E220 (2000)
 
 
}}
 
}}

Revision as of 11:23, November 13, 2018

Notes by user Luis Amaral (Northwestern Univ.) for Dynamic Multi-System Resilience in Human Aging

Post-meeting Reflection

1+ paragraphs on any combination of the following:

  • Presentation highlights
  • Open questions that came up
  • How your perspective changed
  • Impact on your own work
  • e.g. the discussion on [A] that we are having reminds me of [B] conference/[C] initiative/[D] funding call-for-proposal/[E] research group

Fascinating, multi-level, presentations and discussions.

Some points that have come to mind for me. Concerning Dervis' model, I was thinking how having the nodes have an internal structure, that is, each node would have a network structure -- self-similar structure -- would affect the dynamics... I think such an approach would connect nicely to the other presentations concerned with the multi-scale organization of the system.

Concerning the analysis of physiologic signals and the ability to extract different types of information, the site https://physionet.org contains a lot of useful information and may even include a community for discussion of issues (sadly, I haven't worked in this area for a while now).

Ingrid's talk has raised many interesting questions about the different types of models and their different purposes. My thought is that we need research occurring at all types of models with the understanding that each type can contribute to the others. For example, the parametrized, complex climate/ecological models enable us to conduct computational experiments that otherwise would be impossible. However, because of the complexity of the model it is impossible to gain insight on which specific experiments to conduct. Simpler, stylized models, that could be developed and tested against the complex models, could provide the insight to select what computational experiments to conduct.

Reference material notes

Some examples:

  • Here is [A] database on [B] that I pull data from to do [C] analysis that might be of interest to this group (insert link).
  • Here is a free tool for calculating [ABC] (insert link)
  • This painting/sculpture/forms of artwork is emblematic to our discussion on [X]!
  • Schwartz et al. 2017 offers a review on [ABC] migration as relate to climatic factors (add the reference as well).

The Goldberger et al papers review of the Physionet resource and some of the types of analysis that we were performing in the lat 1990s. The Fukuda et al reviews a particular approach to deal with nonstationary time series.

The Amaral et al PNAS presents a simplified network model for generating complex dynamics.

The Amaral PNAS reviews the use cartographic representations of large, complex multilevel networks to summarize information on those network and gain insight.

The Goyal and Maslov paper proposes a model for explaining the structure and resilience of microbial communities. The Stouffer et al papers discusses models of food web structure.

Reference Materials

Title Author name Source name Year Citation count From Scopus. Refreshed every 5 days. Page views Related file
Heuristic segmentation of a nonstationary time series Kensuke Fukuda, H. Eugene Stanley, Luis A.Nunes Amaral Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2004 36 2
Diversity, Stability, and Reproducibility in Stochastically Assembled Microbial Ecosystems Akshit Goyal, Sergei Maslov Physical Review Letters 2018 21 4
Social embeddedness in an online weight management programme is linked to greater weight loss Julia Poncela-Casasnovas, Bonnie Spring, Daniel McClary, Arlen C. Moller, Rufaro Mukogo, Christine A. Pellegrini, Michael J. Coons, Miriam Davidson, Satyam Mukherjee, Luis A.Nunes Amaral Journal of the Royal Society Interface 2015 19 0
PhysioBank, PhysioToolkit, and PhysioNet : Components of a New Research Resource for Complex Physiologic Signals 0 17
Fractal dynamics in physiology: Alterations with disease and aging 0 6
Emergence of complex dynamics in a simple model of signaling networks 0 2
A robust measure of food web intervality 0 2
A truer measure of our ignorance 0 4