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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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SNPdbe: constructing an nsSNP functional impacts database.

Christian Schaefer1, Alice Meier, Burkhard Rost

  • 1Technische Universitaet Muenchen, Bioinformatics - I12, Informatik, Boltzmannstrasse 3, Muenchen, Germany. schaefer@rostlab.org

Bioinformatics (Oxford, England)
|January 3, 2012
PubMed
Summary
This summary is machine-generated.

SNPdbe-SNP is a new database that predicts the functional impact of single nucleotide polymorphisms (SNPs). It combines computational predictions with experimental data for over 2600 organisms, aiding in understanding genetic variation.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Existing databases primarily annotate experimentally characterized single nucleotide polymorphisms (SNPs).
  • Most polymorphisms lack experimental annotation of their functional impact.
  • Non-synonymous SNPs (nsSNPs) result in single amino acid substitutions (SAAS) that can alter protein function.

Purpose of the Study:

  • Introduce SNPdbe-SNP, a database predicting the functional impacts of SNPs.
  • Provide computationally annotated functional impacts for nsSNPs.
  • Integrate diverse data sources for comprehensive SNP effect prediction.

Main Methods:

  • Utilized SNAP and SIFT algorithms for predicting SAAS impact on protein function.
  • Augmented predictions with experimental function/structure data.
  • Integrated disease associations from PMD, OMIM, and UniProt.

Main Results:

  • Database entries include nsSNPs from dbSNP, 1000 Genomes, UniProt, and PMD.
  • Covers SAASs from over 2600 organisms, with a focus on human variants.
  • Provides predicted functional impacts alongside experimental and disease association data.

Conclusions:

  • SNPdbe-SNP offers a valuable resource for understanding the functional consequences of genetic variations.
  • The database is continuously updated and expandable with new information sources.
  • Accessible via an MySQL dump and a web interface for flexible searching.