Oct 28, 2013 · We use two feature selection algorithms to identify 16 features, out of a total of 560 physicochemical properties, presumably important to protein aggregation.
Oct 28, 2013 · We use two feature selection algorithms to identify 16 features, out of a total of 560 physicochemical properties, presumably important to ...
The APR-Score offers a valuable tool for researchers investigating protein aggregation-related diseases, as it can expedite the identification of ...
Results: We use two feature selection algorithms to identify 16 features, out of a total of 560 physicochemical properties, presumably important to protein ...
We use two feature selection algorithms to identify 16 features, out of a total of 560 physicochemical properties, presumably important to protein aggregation.
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Identification of properties important to protein aggregation using feature selection. Overview of attention for article published in BMC Bioinformatics ...
Identification of properties important to protein aggregation using feature selection ... aggregates sequester numerous metastable proteins with essential ...
Fang et al. Identification of properties important to protein aggregation using feature selection. BMC Bioinformatics. (2013). J.F. Díaz-Villanueva et al ...
For example, 16 features have been selected out of initially 560 physicochemical properties as relevant for protein aggregation [122] . Since these parameter ...
Integrating various features from different protein properties helps to improve the prediction accuracy of protein structural class but need to deal with the ...