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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
GWAS does not require the identification of the target gene involved in...
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Conservative Site-specific Recombination and Phase Variation02:53

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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
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Restarting Stalled Replication Forks02:37

Restarting Stalled Replication Forks

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DNA replication is initiated at sites containing predefined DNA sequences known as origins of replication. DNA is unwound at these sites by the minichromosome maintenance (MCM) helicase and other factors such as Cdc45 and the associated GINS complex.The unwound single strands are protected by replication protein A (RPA) until DNA polymerase starts synthesizing DNA at the 5’ end of the strand in the same direction as the replication fork. To prevent the replication fork from falling apart,...
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
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Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

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In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
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Crossing Over01:34

Crossing Over

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Unlike mitosis, meiosis aims for genetic diversity in its creation of haploid gametes. Dividing germ cells first begin this process in prophase I, where each chromosome—replicated in S phase—is now composed of two sister chromatids (identical copies) joined centrally.
The homologous pairs of sister chromosomes—one from the maternal and one from the paternal genome—then begin to align alongside each other lengthwise, matching corresponding DNA positions in a process...
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Related Experiment Video

Updated: Oct 16, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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ARHap: Association Rule Haplotype Phasing.

Sepideh Mazrouee

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |October 14, 2021
    PubMed
    Summary

    This study introduces ARHap, a novel computational framework for accurate human haplotype phasing. ARHap efficiently discovers hidden genetic relationships to reconstruct individual haplotypes from DNA sequencing data.

    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • Haplotype phasing is crucial for understanding genetic variation and disease association.
    • Existing computational methods for haplotype phasing face challenges in speed and accuracy, especially with complex genomic data.

    Purpose of the Study:

    • To develop a novel, fast, and accurate computational framework for individual human haplotype phasing.
    • To leverage association rule learning for discovering inter-allelic dependencies and improving haplotype reconstruction.

    Main Methods:

    • ARHap framework utilizes two modules: association rule learning and haplotype reconstruction.
    • Association rule learning identifies quantitative rules from DNA reads to reveal allele inter-dependencies.
    • An incremental and adaptive approach refines rules based on unreconstructed single nucleotide polymorphism (SNP) sites for accurate haplotype construction.

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    Main Results:

    • ARHap demonstrates superior performance in diploid haplotyping compared to state-of-the-art algorithms.
    • Experimental analyses show significant improvements in both speed and accuracy of haplotype phasing.
    • The adaptive strategy effectively eliminates irrelevant or erroneous rules, enhancing final haplotype reliability.

    Conclusions:

    • ARHap offers a significant advancement in read-based computational haplotype phasing.
    • The framework's novel approach to rule discovery and adaptive reconstruction leads to high accuracy and efficiency.
    • ARHap provides a powerful tool for genomic research requiring precise individual haplotype information.