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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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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Related Experiment Video

Updated: Nov 5, 2025

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
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Writing python programs to map alleles related to genetic disease.

Quinn Allbee1, Robert Barber1

  • 1University of Wisconsin-Parkside, Kenosha, Wisconsin, USA.

Biochemistry and Molecular Biology Education : a Bimonthly Publication of the International Union of Biochemistry and Molecular Biology
|May 15, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a Python programming activity for biology students to identify disease-linked alleles. It enhances understanding of gene structure and programming skills in a distance learning context.

Keywords:
bioinformaticsbiologycomputer programminggeneticsmolecularpython

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Area of Science:

  • Computational Biology
  • Genetics
  • Bioinformatics

Background:

  • Biology increasingly relies on data analysis and computational tools.
  • Integrating programming into biology curricula is essential for modern scientific training.
  • Distance learning requires adaptable and engaging educational activities.

Purpose of the Study:

  • To describe an introductory programming activity for biology students.
  • To facilitate the identification of disease-linked alleles using Python.
  • To support distance learning environments with experiential learning.

Main Methods:

  • Students develop Python programs to analyze genetic data.
  • The activity focuses on identifying the nature of alleles linked to specific diseases.
  • Provided datasets include mapped alleles for the CFTR and HFE genes.

Main Results:

  • The activity effectively engages students in problem-solving.
  • Students apply basic programming skills to biological questions.
  • The exercise enhances comprehension of eukaryotic gene structure.

Conclusions:

  • This experiential programming activity is suitable for distance learning.
  • It provides a practical approach to learning computational biology and genetics.
  • The provided resources allow for modifications and further student exercises.