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Related Concept Videos

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...
Genetic Screens02:46

Genetic Screens

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.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
Genetic Variation01:25

Genetic Variation

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.
Genes exist in different versions called alleles, which...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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.
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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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Related Experiment Video

Updated: Jun 22, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Variable selection and dependency networks for genomewide data.

Adrian Dobra1

  • 1Department of Statistics and Department of Biobehavioral Nursing and Health Systems, University of Washington Seattle, WA 98195, USA. adobra@u.washington.edu

Biostatistics (Oxford, England)
|June 13, 2009
PubMed
Summary
This summary is machine-generated.

A new bounded mode stochastic search (BMSS) algorithm aids in variable selection, classification, and building sparse dependency networks. This method effectively determines genetic networks from complex, genomewide data involving mixed variable types.

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

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Last Updated: Jun 22, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

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

Area of Science:

  • Computational Biology
  • Statistical Modeling
  • Bioinformatics

Background:

  • Linear regression models are fundamental in statistical analysis.
  • Variable selection and network construction are crucial for understanding complex biological systems.
  • Existing methods may struggle with mixed continuous and discrete variables in genomewide data.

Purpose of the Study:

  • Introduce a novel stochastic search algorithm, bounded mode stochastic search (BMSS).
  • Apply BMSS for variable selection, classification, and sparse dependency network construction.
  • Develop a method to determine genetic networks from genomewide data with mixed variable types.

Main Methods:

  • Developed the bounded mode stochastic search (BMSS) algorithm.
  • Utilized BMSS for variable selection and classification tasks.
  • Applied BMSS to construct sparse dependency networks and infer genetic networks.

Main Results:

  • Demonstrated the efficacy of BMSS in variable selection and classification.
  • Successfully constructed sparse dependency networks using BMSS.
  • Showcased the ability of BMSS to determine genetic networks from mixed-variable genomewide data.
  • Validated the methodology on several real-world datasets.

Conclusions:

  • BMSS is an effective algorithm for linear regression models.
  • The algorithm facilitates robust variable selection, classification, and network inference.
  • BMSS provides a powerful tool for analyzing complex biological data, including genetic networks.