A machine learning approach to estimation of phase diagrams for three-component lipid mixtures.

ABSTRACT: The plasma membrane of eukaryotic cells is commonly believed to contain ordered lipid domains. The interest in understanding the origin of such domains has led to extensive studies on the phase behavior of mixed lipid systems. Three-component phase diagrams, composed of a high melting temperature (Tm) lipid, cholesterol, and a low Tm lipid have been valuable in studying lipid phase behavior. However, developing phase diagrams over the entire composition space and with precise tie-lines requires significant experimental effort. In this study, a machine learning approach was used to predict the Tm of lipids and generate phase diagrams from lipid mixtures. First, artificial neural network (ANN) was used for the prediction of Tm. The network was trained using available Tm data and was able to

SUBMITTER: Aghaaminiha M 

PROVIDER: S-EPMC7301216 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature