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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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%...
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Single Nucleotide Polymorphisms-SNPs01:05

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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,...
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Mismatch Repair01:20

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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
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The basic reaction of homologous recombination (HR) involves two chromatids that contain DNA sequences sharing a significant stretch of identity. One of these sequences uses a strand from another as a template to synthesize DNA in an enzyme-catalyzed reaction. The final product is a novel amalgamation of the two substrates. To ensure an accurate recombination of sequences, HR is restricted to the S and G2 phases of the cell cycle. At these stages, the DNA has been replicated already and the...
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Genome-wide Association Studies-GWAS01:11

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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.
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Rare Event Detection Using Error-corrected DNA and RNA Sequencing
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Efficient fast heuristic algorithms for minimum error correction haplotyping from SNP fragments.

Maryam Pourkamali Anaraki1, Mehdi Sadeghi2

  • 1Department of Computer Engineering, Science and Research Branch, Islamic Azad University, P.O. Box 14515/775, Tehran, Iran.

International Journal of Computational Biology and Drug Design
|December 26, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational approach for reconstructing human haplotypes from single nucleotide polymorphism (SNP) fragments. The method efficiently solves the complex haplotype reconstruction problem using clustering techniques, improving accuracy in genetic studies.

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Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Human Genetics

Background:

  • Complete human genome data is essential for genetic studies linking genomes to complex diseases.
  • Haplotypes, sets of single nucleotide polymorphisms (SNPs) on a chromosome, hold significant potential for disease association studies, natural selection analysis, and identifying recombination hotspots.

Purpose of the Study:

  • To present a novel computational approach for reconstructing paternal and maternal haplotypes from SNP fragments.
  • To address the NP-hard problem of haplotype reconstruction within the Minimum Error Correction (MEC) model.

Main Methods:

  • Developed a novel approach utilizing two fast and accurate clustering techniques.
  • These techniques form the core of the procedure to efficiently solve the ill-defined haplotype reconstruction problem in the MEC model.

Main Results:

  • The proposed methods demonstrate efficiency and accuracy in haplotype reconstruction.
  • Performance was validated against conventional methods using two real benchmark datasets: ACE and DALY.

Conclusions:

  • The novel clustering-based approach provides an efficient and accurate solution for haplotype reconstruction from SNP fragments.
  • This advancement is crucial for enhancing genetic studies, including disease association and evolutionary analyses.