A computational approach for detecting moonlighting proteins (MPs) from GO annotations or omics-based features. MPFit can be applied to a large fraction of proteins in a genome due to the use of several omics-based features and the implemented imputation protocol for filling missing features. The overall computational prediction model undergoes four phases: data construction, feature computation, missing feature imputation (when needed) and classification into moonlighting protein or non-moonlighting protein.
Predicts moonlighting proteins (MP) from text information. DextMP finds textual information about proteins: titles, abstract from literature and function description in Uniprot entries. This software’s functioning consists of four steps: (1) extraction from literature, (2) construction of k-dimensional feature vector, (3) classification to MP or to non-MP based on text features and finally (4) prediction to the protein.
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