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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Factors Influencing Drug Absorption: Disease States and Pharmacology01:25

Factors Influencing Drug Absorption: Disease States and Pharmacology

Multiple disease states can significantly influence the oral drug absorption process by affecting blood flow and the functionality of the gastrointestinal (GI) system. Various GI diseases, including conditions that alter GI motility, such as diarrhea, decreased acid secretions (achlorhydria), and infections, have been associated with reduced drug absorption.
Substances such as alcohol and specific drugs, including antineoplastics, can also negatively impact drug absorption. For instance,...
Factors Affecting Illness01:18

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness, disability,...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

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...
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...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...

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Related Experiment Video

Updated: May 20, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

CIDeR: multifactorial interaction networks in human diseases.

Martin Lechner, Veit Höhn, Barbara Brauner

    Genome Biology
    |July 20, 2012
    PubMed
    Summary
    This summary is machine-generated.

    The CIDeR database integrates information on metabolic and neurological disorders, detailing 18,813 interactions. This resource aids biologists in understanding complex disease networks and systems biology.

    Related Experiment Videos

    Last Updated: May 20, 2026

    Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
    08:51

    Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

    Published on: September 20, 2024

    Area of Science:

    • Bioinformatics
    • Systems Biology
    • Genomics

    Background:

    • Complex diseases arise from intricate interactions between various factors.
    • Understanding these interactions is crucial for disease pathobiology research.

    Purpose of the Study:

    • To introduce CIDeR, a manually curated, integrative database for metabolic and neurological disorders.
    • To provide a structured resource for studying disease-related molecular, bioprocess, and environmental interactions.

    Main Methods:

    • Manual curation of scientific literature to extract experimentally validated interactions.
    • Development of an interactive graphical representation for disease networks.
    • Systematic annotation of data within the CIDeR database.

    Main Results:

    • CIDeR contains 18,813 experimentally validated interactions.
    • The database covers interactions involving molecules, bioprocesses, and environmental factors.
    • Interactive network visualizations are available for disease-related data.

    Conclusions:

    • CIDeR serves as a versatile knowledge base for biologists.
    • The database supports the analysis of large-scale data and systems biology approaches.
    • CIDeR facilitates a deeper understanding of complex disease networks.