High-Fidelity Design of Multimodal Restorative Interventions in Gulf War Illness

Abstract

We have made progress towards the overall objectives of the grant and laid a foundation for future work. Specially, we improved an optimization tool for constraint satisfaction that isused to mathematically optimize models of biological regulatory networks. We also worked with Dr. Brodericks team to apply these methods to specific biological networks. We hadpreviously optimized new regulatory networks that can capture cyclic behavior in the Hypothalamic-Pituitary Adrenal (HPA) axis model. We have now developed models of other types of biological regulatory networks. Currently, the methods that the team has developed work only on discrete finite models. Our last major research task was to apply machine learning methods to model discovery for models using continuous parameter models.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2019
Accession Number
AD1097356

Entities

People

  • Darrell Whitley

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Computer Science
  • Artificial Intelligence
  • Cell Physiological Processes
  • Computational Biology
  • Computational Science
  • Computations
  • Computer Science
  • Intervention
  • Learning
  • Machine Learning
  • Mathematical Models
  • Neural Networks
  • Optimization
  • Persian Gulf Syndrome
  • Reliability
  • Systems Biology

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Gulf War Illness and Chronic Multisymptom Illness in Veterans.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms