Attractor Signaling Models for Discovery of Combinatorial Therapies

Abstract

The objective of this project consists in demonstrating that attractor models increase the chances of discovering combinations of many drugs with strong synergistic effects in lung cancer. The approach will be tested using a high throughput screening facility to compare the therapeutic effectiveness of random combinations and combinations predicted to be effective by the model.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA603960

Entities

People

  • Carlo Piermarocchi

Organizations

  • Michigan State University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Cancer
  • Cells
  • Computational Biology
  • Computational Science
  • Databases
  • Information Science
  • Lung Cancer
  • Lymphatic Diseases
  • Machine Learning
  • Neoplasms
  • Neural Networks
  • Predictive Modeling
  • Proteins
  • Statistical Algorithms
  • Stem Cells
  • Systems Biology

Readers

  • Computational Modeling and Simulation
  • Immunology and Pathology
  • Oncology and Biomarker-Based Cancer Detection.