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Three-Compartment Open Model01:06

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The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
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Molecular Models02:00

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Two-Compartment Open Model: Overview01:05

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Multicompartmental models are crucial tools in pharmacokinetics, providing a framework to understand how drugs move within the body. The two-compartment model is a crucial subtype, segmenting the body into central and peripheral compartments. The central compartment represents areas with high blood flow, such as plasma and highly perfused organs like the kidneys and liver, while the peripheral compartment signifies tissues with lower blood flow, like adipose tissue and muscle tissue.
The...
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Ligand Binding and Linkage00:49

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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Video Experimental Relacionado

Updated: Jan 8, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
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LinkML: Un marco de modelado de datos abierto

Sierra A T Moxon1, Harold Solbrig2, Nomi L Harris1

  • 1Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

GigaScience
|December 12, 2025
PubMed
Resumen
Este resumen es generado por máquina.

LinkML (Linked Data Modeling Language) es un marco abierto que estandariza los datos en su origen, mejorando la interoperabilidad y el cumplimiento de los datos FAIR. Este enfoque simplifica la integración, validación y el intercambio de datos en diversos campos científicos.

Palabras clave:
datos listos para IAmodelado de datosdatos FAIRintegración de datosontologíasdatos abiertoscódigo abiertoesquemamodelado semántico

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Área de la Ciencia:

  • Ciencia de datos
  • Biología computacional
  • Gestión de la información

Sus antecedentes:

  • Los datos científicos a menudo no están estructurados (por ejemplo, cuadernos de texto libre, hojas de cálculo), lo que dificulta la interoperabilidad.
  • La falta de estandarización de datos complica la integración, validación y reutilización.
  • Los modelos de datos existentes pueden ser complejos y conducir a la proliferación de formatos de un solo uso.

Objetivo del estudio:

  • Presentar LinkML (Linked Data Modeling Language) como una solución para la estandarización de datos.
  • Demostrar la capacidad de LinkML para simplificar la creación, validación e intercambio de datos.
  • Promover la adopción de LinkML para mejorar la interoperabilidad de los datos y el cumplimiento de FAIR.

Principales métodos:

  • Utiliza un marco abierto con una sintaxis accesible para describir esquemas de datos, clases y relaciones.
  • Admite diversas estructuras de datos, desde listas simples hasta modelos complejos y normalizados con herencia.
  • Permite la integración perfecta con marcos existentes y la importación de esquemas.

Principales resultados:

  • LinkML permite la creación de estructuras de datos bien definidas, estables y alineadas con ontologías.
  • Facilita la colaboración interdisciplinaria a través de semánticas de datos accesibles.
  • Simplifica el proceso de definición y compartición de modelos de datos.

Conclusiones:

  • LinkML reduce la heterogeneidad y complejidad de los datos, promoviendo los estándares de datos FAIR.
  • Tiene una amplia adopción en diversos dominios científicos y comerciales.
  • LinkML hace que los modelos de datos implícitos sean explícitos y computables, estandarizando los datos en su origen.