Model refinement is the process of improving a computational model's accuracy and reliability by iteratively adjusting its parameters and structures based on new data or insights. This step is crucial in ensuring that the predictions made by the model closely align with experimental or observed data, particularly in fields like molecular biology where understanding protein structure and function is essential.
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