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Discrete dynamic modeling: A network approach for systems pharmacology
Steven Nathaniel Steinway
, Rui Sheng Wang
,
Reka Albert
Physics
Huck Institutes of the Life Sciences
Penn State Cancer Institute
Cancer Institute, Experimental Therapeutics
Research output
:
Chapter in Book/Report/Conference proceeding
›
Chapter
6
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Scopus citations
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Dive into the research topics of 'Discrete dynamic modeling: A network approach for systems pharmacology'. Together they form a unique fingerprint.
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Keyphrases
Dynamic Model
100%
Network Approach
100%
Discrete Dynamics
100%
Epidermis
75%
Tumor Growth
50%
Regulatory Relationship
50%
Protein Molecules
25%
Small Molecules
25%
Signaling Pathway
25%
Signal Transduction Pathway
25%
Mathematical Model
25%
Genetic Differences
25%
Pharmacodynamic Model
25%
Drug Effects
25%
Paucity
25%
Knowledge Gaps
25%
Drug Development
25%
Discrete Model
25%
Deregulation
25%
Predictive Models
25%
Biological Systems
25%
Cellular Networks
25%
Kinetic Parameters
25%
Experimental Tools
25%
Growth Hormone Receptor
25%
Three-state Model
25%
Systems Biology
25%
Boolean Model
25%
Gefitinib
25%
Growth Factor Receptor Inhibitors
25%
Static Networks
25%
Growth Factor Receptor Signaling
25%
Genomic Variants
25%
Interaction Information
25%
Variable Drug Response
25%
Qualitative Interaction
25%
Relative Information
25%
Discrete Dynamic Model
25%
Biochemistry, Genetics and Molecular Biology
Growth Factor Receptor
100%
Tumor Progression
100%
Protein
50%
Small Molecule
50%
Signal Transduction
50%
Genetic Difference
50%
Dynamics
50%
Drug Effect
50%
Pharmacodynamics
50%
Drug Response
50%
Kinetic Parameter
50%
Gefitinib
50%
Growth Factor Receptor Inhibitor
50%
Genomics
50%
Pharmacology, Toxicology and Pharmaceutical Science
Dynamic Modeling
100%
Growth Factor Receptor
75%
Tumor Growth
50%
Diseases
50%
Drug Development
25%
Pharmacodynamics
25%
Gefitinib
25%
Neuroscience
Gefitinib
50%
Growth Factor Receptor Inhibitor
50%