caa a22 4500 605512213 CHVBK 20210128100654.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00894-015-2794-y doi (NATIONALLICENCE)springer-10.1007/s00894-015-2794-y Computational approaches to study the effects of small genomic variations [Elektronische Daten] [Kamil Khafizov, Maxim Ivanov, Olga Glazova, Sergei Kovalenko] Advances in DNA sequencing technologies have led to an avalanche-like increase in the number of gene sequences deposited in public databases over the last decade as well as the detection of an enormous number of previously unseen nucleotide variants therein. Given the size and complex nature of the genome-wide sequence variation data, as well as the rate of data generation, experimental characterization of the disease association of each of these variations or their effects on protein structure/function would be costly, laborious, time-consuming, and essentially impossible. Thus, in silico methods to predict the functional effects of sequence variations are constantly being developed. In this review, we summarize the major computational approaches and tools that are aimed at the prediction of the functional effect of mutations, and describe the state-of-the-art databases that can be used to obtain information about mutation significance. We also discuss future directions in this highly competitive field. Springer-Verlag Berlin Heidelberg, 2015 Bioinformatics nationallicence Computational methods nationallicence Single-nucleotide polymorphism nationallicence Coding SNP nationallicence Mutation databases nationallicence TCGA : The Cancer Genome Atlas nationallicence ICGC : International Cancer Genome Consortium nationallicence SNP : Single nucleotide polymorphism nationallicence HGMD : Human Gene Mutation Database nationallicence sSNP : Nonsynonymous SNP nationallicence OMIM : Online Mendelian Inheritance in Man nationallicence HGV : Human Genome Variation nationallicence PMD : Protein Mutant Database nationallicence EVS : Exome Variant Server nationallicence COSMIC : Collection of somatic mutations in cancer nationallicence NCBI : National Center for Biotechnology Information nationallicence dbSNP : SNP Database nationallicence LSDB : Large number of locus-specific databases nationallicence HGVS : Human Genome Variation Society nationallicence MAF : Minor allele frequency nationallicence MSA : Multiple sequence alignment nationallicence PDB : Protein Data Bank nationallicence SS : Secondary structure nationallicence CAGI : Critical Assessment of Genome Interpretation nationallicence Khafizov Kamil Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut Ivanov Maxim Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut Glazova Olga Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut Kovalenko Sergei Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut Journal of Molecular Modeling Springer Berlin Heidelberg 21/10(2015-10-01), 1-14 1610-2940 21:10<1 2015 21 894 https://doi.org/10.1007/s00894-015-2794-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 review-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00894-015-2794-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Khafizov Kamil Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut NATIONALLICENCE 700 1- Ivanov Maxim Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut NATIONALLICENCE 700 1- Glazova Olga Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut NATIONALLICENCE 700 1- Kovalenko Sergei Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation aut NATIONALLICENCE 773 0- Journal of Molecular Modeling Springer Berlin Heidelberg 21/10(2015-10-01), 1-14 1610-2940 21:10<1 2015 21 894