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Related Concept Videos

Prodrugs01:30

Prodrugs

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Prodrugs are a class of pharmaceutical compounds that undergo a biotransformation process within the body to be converted into a pharmacologically active drug. Prodrugs are designed to improve the therapeutic properties of the parent drug, such as enhancing bioavailability, increasing stability, or reducing toxicity. The concept of prodrugs revolves around modifying the chemical structure of the original drug to make it more effective or convenient for administration.
Prodrugs help overcome...
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Drug Nomenclature01:17

Drug Nomenclature

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During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that...
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Propagation of Action Potentials01:23

Propagation of Action Potentials

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The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
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IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

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Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the  phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and...
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Methods of Medium Optimization01:28

Methods of Medium Optimization

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Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
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Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Related Experiment Video

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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ProphNet: a generic prioritization method through propagation of information.

Víctor Martínez, Carlos Cano, Armando Blanco

    BMC Bioinformatics
    |February 26, 2014
    PubMed
    Summary

    ProphNet is a novel network-based prioritization tool that integrates diverse biological entities for enhanced hypothesis generation. It significantly improves sensitivity and specificity in gene-disease and domain-disease prioritization tasks.

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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Systems Biology

    Background:

    • Network-based prioritization tools are valuable for hypothesis generation in early research.
    • Existing tools are limited to specific domains (e.g., gene-disease) and networks with few entity types.
    • This limits their application to new prioritization tasks.

    Purpose of the Study:

    • To present ProphNet, a generic network-based prioritization tool.
    • To enable integration of an arbitrary number of interrelated biological entities.
    • To accomplish any prioritization task.

    Main Methods:

    • ProphNet integrates information from heterogeneous networks with multiple biological entity types.
    • It ranks entities by propagating information and measuring correlations between query and target sets.
    • The method is applicable to any prioritization task.

    Main Results:

    • ProphNet demonstrated significant improvements in sensitivity and specificity compared to existing methods (rcNet, DomainRBF).
    • Performance was validated in gene-disease and domain-disease prioritization tasks.
    • Applied to Alzheimer's, Diabetes Mellitus Type 2, and Breast Cancer, ProphNet identified putative candidate genes.

    Conclusions:

    • ProphNet is a versatile tool for prioritizing biological entities within complex, heterogeneous networks.
    • It effectively integrates diverse biological information for hypothesis generation.
    • The tool is available online with a Matlab implementation.