Frontiers in ChemistryBioinformaticsPeer-reviewed journal article
Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases
Francesco OlivaiD, Francesco MusianiiD, Alejandro GiorgettiiD, Silvia De RubeisiD, Oksana SorokinaiD, J. Douglas ArmstrongiD, Paolo CarloniiD, Paolo RuggeroneiD
Abstract
The seamless integration of human disease-related mutation data into protein structures is an essential component of any attempt to correctly assess the impact of the mutation. The key step preliminary to any structural modelling is the identification of the correct isoform onto which mutations should be mapped because there are several functionally different protein isoforms from the same gene. To handle large sets of data coming from omics techniques, this challenging task should be automatized. Here we present our code MoNvIso (Modelling eNvironment for Isoforms), which pinpoints the correct isoform associated with the mutation of interest and builds a structural model of both the wild type isoform and the related variants starting from the name of the gene and the list of mutations of interest.
- organism: human
- assay: protein structure
- research focus: protein structure prediction
- approach: statistical model
- Citations
- 1
- FWCI
- 0.09
- Field percentile
- 28th percentile
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