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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,...
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...
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

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Related Experiment Video

Updated: Jun 27, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases.

Jin Ok Yang1, Sohyun Hwang, Jeongsu Oh

  • 1Korean BioInformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 305-806, Korea. joy@kribb.re.kr

BMC Bioinformatics
|December 19, 2008
PubMed
Summary

This study developed an integrated database and pipeline system to analyze the relationship between single nucleotide polymorphisms (SNPs) and diseases. The system aids researchers in identifying disease-associated genes and SNP markers for genetic studies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Medical Genetics

Background:

  • Genetic variations, like single nucleotide polymorphisms (SNPs), play a crucial role in disease development by affecting biological regulation.
  • Existing databases often lack comprehensive integration of gene, SNP, and disease information, hindering correlation studies.
  • A unified resource is needed to capture the complex relationships among genes, SNPs, and diseases.

Purpose of the Study:

  • To develop an integrated database-pipeline system for studying the association between SNPs and human diseases.
  • To provide a centralized resource for gene, SNP, and disease-related information.
  • To facilitate the identification of candidate genes and SNP markers for disease association studies.

Main Methods:

  • Standardized gene and disease nomenclature using Unified Medical Language System (UMLS), HUGO Gene Nomenclature Committee (HGNC), and NCBI databases.
  • Integrated data from multiple public databases for genes (NCBI mRNA, UniProt), genetic variants (dbSNP, JSNP), and diseases (OMIM, GAD).
  • Developed a web-accessible database and genome browser for data retrieval and visualization.

Main Results:

  • Successfully unified gene and disease terms, integrating data from diverse sources into a cohesive system.
  • The developed database-pipeline system provides a disease thesaurus linking genes and SNPs to specific diseases.
  • A web interface and genome browser are available for exploring disease-associated SNPs and genes, facilitating the review of potentially deleterious variants.

Conclusions:

  • The system effectively captures relationships between disease-associated SNPs and disease-causing genes.
  • Provides a valuable resource for both epidemiological and molecular biological approaches to disease-gene association studies.
  • The database contains 14,674 SNP and 109,715 gene records, aiding economical and efficient disease association research.