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Related Concept Videos

Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...

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Related Experiment Video

Updated: Jun 24, 2026

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

A dynamic network approach for the study of human phenotypes.

César A Hidalgo1, Nicholas Blumm, Albert-László Barabási

  • 1Center for International Development and Harvard Kennedy School, Harvard University, Cambridge, Massachusetts, United States of America.

Plos Computational Biology
|April 11, 2009
PubMed
Summary

This study introduces a large Phenotypic Disease Network (PDN) revealing how disease progression relates to network structure. Findings show disease relationships and patient demographics impact illness evolution and mortality risk.

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Area of Science:

  • Computational biology
  • Network science
  • Medical informatics

Background:

  • Integrating multi-omics data is crucial for understanding disease origins.
  • Previous research has explored disease relationships but lacked large-scale phenotypic data.

Purpose of the Study:

  • To introduce a novel Phenotypic Disease Network (PDN) derived from extensive patient data.
  • To investigate the relationship between network structure and disease progression, mortality, and demographic factors.

Main Methods:

  • Construction of a PDN using disease history data from over 30 million patients.
  • Analysis of network topology to identify correlations between disease relationships and patient outcomes.
  • Examination of disease progression patterns across different genders and ethnicities.

Main Results:

  • Patients develop diseases proximate to existing conditions within the PDN.
  • Disease progression varies by gender and ethnicity.
  • Highly connected diseases in the PDN correlate with increased mortality.
  • Diseases preceding others in the network are more connected and linked to higher mortality.

Conclusions:

  • Network analysis of phenotypic data offers insights into disease origins and evolution.
  • The PDN provides a valuable resource for studying human disease progression.
  • Understanding disease network structures can potentially improve patient outcomes and personalized medicine.