Concentration optimization of combinatorial drugs using Markov chain-based models

Concentration optimization of combinatorial drugs using Markov chain-based models

Background: Combinatorial drug therapy for complex diseases, such as HSV infection and cancers, has a more significant efficacy than single-drug treatment. However, one key challenge is how to effectively and efficiently determine the optimal concentrations of combinatorial drugs because the number...

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Bibliographic Details
Main Authors: Dang, D. (Author), Liu, L. (Author), Ma, S. (Author), Wang, W. (Author), Wang, Y. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Benchmarking
Bioinformatics
Biological experiments
Combinatorial drug optimization
Combinatorial therapy
computer simulation
Computer Simulation
Diagnosis
Disease control
Diseases
drug combination
Drug Combinations
Drug concentration
Drug therapy
Markov chain
Markov chain process
Markov chains
Markov Chains
Optimal concentration
Optimization
Parallel implementations
probability
Probability
Probability distributions
Stationary balance distribution
Stationary distribution
Stochastic optimization algorithm
Transition probability
Transition probability matrix
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