A review study: Computational techniques for expecting the impact of non-synonymous single nucleotide variants in human diseases

Article ID	Journal	Published Year	Pages	File Type
10212414	Gene	2019	14 Pages	PDF

Abstract

This review is targeted at bioinformaticians attentive in the characterization of regulatory variants, geneticists, molecular biologists attentive in understanding more about the nature and effective role of such variants from a functional point of views, and clinicians who may hope to learn about variants in human associated with a specific disease and find out what to do next to uncover how they impact on the underlying mechanisms.

Keywords

polymorphism phenotyping v2 Chasm ACC MCC PAPI ANN LMT Psic RBF SIFT iFISH AUC Protein Variation Effect Analyzer Abbreviation HOPE Protein ANalysis THrough Evolutionary Relationships Pseudo amino acid composition Combined Annotation Dependent Depletion Machine learning techniques Random forest Annotation Accuracy Artificial Neural Network SNAP Phenotype Predictive power Support vector machine SVM SDM area under the curve Gene ontology Pathogenic PANTHER Protein stability PROVEAN PolyPhen-2 Genotype