Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Commentary: model building, quantitative testing, and model comparison.

E B Klerman1, M E Jewett

  • 1Dept. of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA 02115, USA.

Journal of Biological Rhythms
|January 22, 2000
PubMed
Summary

This study proposes developing physiological mathematical models by comparing various mathematical structures. Careful selection of systems and data is crucial for accurate model formulation and validation.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mammalian rest/activity patterns explained by physiologically based modeling.

PLoS computational biology·2013
Same author

Arousal state feedback as a potential physiological generator of the ultradian REM/NREM sleep cycle.

Journal of theoretical biology·2012
Same author

Photic resetting of the human circadian pacemaker in the absence of conscious vision.

Journal of biological rhythms·2002
Same author

Absence of an increase in the duration of the circadian melatonin secretory episode in totally blind human subjects.

The Journal of clinical endocrinology and metabolism·2001
Same author

EEG delta activity during undisturbed sleep in the squirrel monkey.

Sleep research online : SRO·2001
Same author

Circadian rhythms of women with fibromyalgia.

The Journal of clinical endocrinology and metabolism·2001

Area of Science:

  • Physiological modeling
  • Mathematical biology
  • Systems physiology

Background:

  • Developing accurate mathematical models requires integrating current physiological knowledge.
  • Experimental data is essential for validating and refining these models.

Discussion:

  • Consideration of diverse mathematical structures is key for robust model formulation.
  • Formal comparison with existing literature models aids in evaluating new approaches.
  • System specificity and data set representativeness are critical for meaningful comparisons.

Key Insights:

  • Mathematical models should be grounded in physiological understanding.
  • Comparative analysis of different mathematical structures enhances model development.
  • Rigorous methodology in system and data selection ensures model reliability.
Keywords:
NASA Discipline Regulatory PhysiologyNon-NASA Center

Related Experiment Videos

Outlook:

  • Future work should focus on refining comparative methodologies for physiological models.
  • Advancing the integration of experimental data into mathematical frameworks.
  • Developing standardized approaches for model validation across different physiological systems.