{"title":"Tools, resources and databases for SNPs and indels in sequences: a review.","authors":"Abhik Seal, Arun Gupta, M Mahalaxmi, Riju Aykkal, Tiratha Raj Singh, Vadivel Arunachalam","doi":"10.1504/IJBRA.2014.060762","DOIUrl":null,"url":null,"abstract":"<p><p>Single Nucleotide Polymorphism (SNP) is a mutation where, a single base in the DNA differs from the usual base at that position. SNPs are the marker of choice in genetic analysis and also useful in locating genes associated with diseases. SNPs are important and frequently occurring point mutations in genomes and have many practical implications. In silico methods are easy to study the SNPs that are occurring in known genomes or sequences of a species of interest during the post genomic era. There are many on-line and stand alone tools to analyse the SNPs. We intend to guide the reader with the software details such as algorithmic background, file requirements, operating system specificity and species specificity, if any, for the tools of SNPs detection in plants and animals. We also list many databases and resources available today to describe SNPs in wide range of organisms. </p>","PeriodicalId":35444,"journal":{"name":"International Journal of Bioinformatics Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJBRA.2014.060762","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Bioinformatics Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBRA.2014.060762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 16
Abstract
Single Nucleotide Polymorphism (SNP) is a mutation where, a single base in the DNA differs from the usual base at that position. SNPs are the marker of choice in genetic analysis and also useful in locating genes associated with diseases. SNPs are important and frequently occurring point mutations in genomes and have many practical implications. In silico methods are easy to study the SNPs that are occurring in known genomes or sequences of a species of interest during the post genomic era. There are many on-line and stand alone tools to analyse the SNPs. We intend to guide the reader with the software details such as algorithmic background, file requirements, operating system specificity and species specificity, if any, for the tools of SNPs detection in plants and animals. We also list many databases and resources available today to describe SNPs in wide range of organisms.
期刊介绍：
Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.
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