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Related Concept Videos

Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Comparing Copy Number Variations and SNPs02:26

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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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Pharmacogenomics: Identification of New Drug Targets01:29

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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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Pharmacogenetics and Pharmacogenomics: Overview01:29

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Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
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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.
GWAS does not require the identification of the target gene involved in...
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Related Experiment Video

Updated: Apr 18, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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An integrative approach to predicting the functional effects of non-coding and coding sequence variation.

Hashem A Shihab1, Mark F Rogers2, Julian Gough2

  • 1MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK, Bristol Centre for Systems Biomedicine, University of Bristol, Bristol BS8 2BN, UK, Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK, Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK and Institute of Medical Genetics, Cardiff University, Cardiff CF14 4XN, UK.

Bioinformatics (Oxford, England)
|January 14, 2015
PubMed
Summary

We developed FATHMM-MKL, a new method to predict the functional impact of genetic variants. This tool outperforms existing algorithms for non-coding variants and offers a confidence score for predictions.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Technological advancements allow identification of numerous human genome variants.
  • Many variants are linked to monogenic diseases or complex traits.

Purpose of the Study:

  • To propose an integrative approach, FATHMM-MKL, for predicting the functional consequences of genetic variants.
  • To leverage diverse genomic annotations and learn their significance.

Main Methods:

  • Developed FATHMM-MKL, an integrative method for variant effect prediction.
  • Utilized multiple genomic annotation sources.
  • Employed a machine learning approach to weight annotation significance.

Main Results:

  • FATHMM-MKL surpasses state-of-the-art methods (CADD, GWAVA) in predicting non-coding variant impact.
  • Performance for coding variants is comparable to leading algorithms.
  • Introduced a confidence measure for ranking variant predictions.

Conclusions:

  • FATHMM-MKL provides a robust tool for assessing variant pathogenicity.
  • The method's performance highlights the utility of integrative genomic annotation analysis.