Single-Nucleotide Polymorphism Bioinformatics

Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis

Since the initial sequencing of the human genome, many projects are underway to understand the effects of genetic variation between individuals. Predicting and understanding the downstream effects of genetic variation using computational methods are becoming increasingly important for single nucleotide polymorphism (SNP) selection in genetics studies and understanding the molecular basis of dis...

Single-nucleotide polymorphism bioinformatics: a comprehensive review of resources.

Single Nucleotide Polymorphism Analysis of Protamine Genes in Infertile Men

Background Single nucleotide polymorphism (SNPs) are considered as one of the underlying causes of male infertility. Proper sperm chromatin packaging which involves replacement of histones with protamines has profound effect on male fertility. Over 20 SNPs have been reported for the protamine 1 and 2. MaterialsAndMethods The aim of this study was to evaluate the frequency of two previously repo...

Single-Nucleotide Polymorphism Masking

Microarrays are widely used to evaluate gene expression at the genome scale. However, all too often the importance of data analysis at the level of the individual probe is overlooked. This is a particular problem when trying to detect differences in gene expression levels among genetically unique animals, across inbred animal strains, or among genetically modified animals. Of particular concern...

Single-nucleotide polymorphism mapping.

Single-nucleotide polymorphism (SNP) mapping is the easiest and most reliable way to map genes in Caenorhabditis elegans. SNPs are extremely dense and usually have no associated phenotype, making them ideal markers for mapping. SNP mapping has three steps. First, recombinant mutant animals are generated over a polymorphic strain (usually CB4856) using standard genetic techniques. Second, the ge...