The CL5D Hybrid Model: A Dynamic Systems Approach to High-Fidelity CRISPR-Cas9 Off-Target Prediction via Conjugate Balance Analysis
The CL5D Hybrid Model: A Dynamic Systems Approach to High-Fidelity CRISPR-Cas9 Off-Target Prediction via Conjugate Balance Analysis
A dynamic systems-based computational model (CL5D Hybrid Model) for predicting CRISPR-Cas9 off-target activity. The framework employs agent-based simulation, phase analysis, and conjugate balance scoring to evaluate editing fidelity beyond static sequence homology. This repository includes the full methodological description and supplementary comparative analysis of ZNF423 and EMX1 target sites.
CL5D model, FOS: Computer and information sciences, Bioinformatics, FOS: Biological sciences, Systems Biology, genome editing fidelity, Genetics, Computational Biology, dynamic systems modeling, CRISPR-Cas9, kinetic proofreading, off-target prediction, conjugate balance
CL5D model, FOS: Computer and information sciences, Bioinformatics, FOS: Biological sciences, Systems Biology, genome editing fidelity, Genetics, Computational Biology, dynamic systems modeling, CRISPR-Cas9, kinetic proofreading, off-target prediction, conjugate balance
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