|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|5519836||1544470||2017||5 صفحه PDF||سفارش دهید||دانلود رایگان|
As computational biology matures as a field, increasing attention is being paid to the relation of computational models to their target. One aspect of this is addressing how computational models can appropriately reproduce the variation seen in experimental data, with one solution being to use populations of models united by a common set of equations (the framework), with each individual member of the population (each model) possessing its own unique set of equation parameters. These model populations are then calibrated and validated against experimental data, and as a whole reproduce the experimentally observed variation. The primary focus of validation thus becomes the population, with the individual models' validation seemingly deriving from their membership of this population. The role of individual models within the population is not clear, with uncertainty regarding the relationship between individual models and the population they make up. This work examines the role of models within the population, how they relate to the population they make up, and how both can be said to be validated in this context.
Journal: Progress in Biophysics and Molecular Biology - Volume 129, October 2017, Pages 20-24