Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

Levels of Use of a GIS01:29

Levels of Use of a GIS

300
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
300
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

240
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
240
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

674
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
674
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

218
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...
218
Introduction to GIS01:28

Introduction to GIS

462
Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
462
Thematic Layering in GIS01:30

Thematic Layering in GIS

292
In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
292

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

[Arthroscopic reconstruction of anterior cruciate ligament with preservation of the remnant bundle].

Zhongguo gu shang = China journal of orthopaedics and traumatology·2013
Same author

[Anterior cruciate ligament reconstruction with tendon graft enveloped by preserved remnants].

Zhongguo gu shang = China journal of orthopaedics and traumatology·2013
Same author

Genetic and molecular biological characterization of two homologous cheR genes from Leptospira interrogans.

Acta biochimica et biophysica Sinica·2013
Same author

Upregulation of glycoprotein nonmetastatic B by colony-stimulating factor-1 and epithelial cell adhesion molecule in hepatocellular carcinoma cells.

Oncology research·2013
Same author

Effect of implantation of biodegradable magnesium alloy on BMP-2 expression in bone of ovariectomized osteoporosis rats.

Materials science & engineering. C, Materials for biological applications·2013
Same author

[Texture variation of CC 5052 aluminum alloy slab from surface to center layer by XRD].

Guang pu xue yu guang pu fen xi = Guang pu·2013
Same journal

STED: flexible cross-modal topic modeling infers cell-type-specific regulatory landscapes from bulk epigenomics.

Briefings in bioinformatics·2026
Same journal

A knowledge-guided deep learning framework for quantitative nucleic acid testing.

Briefings in bioinformatics·2026
Same journal

Optimal transport for label transfer in single-cell multi-omics integration.

Briefings in bioinformatics·2026
Same journal

Continuous multi-omics pathway enrichment analysis resolves hidden functional heterogeneity.

Briefings in bioinformatics·2026
Same journal

Evaluating completeness, coherence, and consistency of genome-scale function annotations.

Briefings in bioinformatics·2026
Same journal

Transformers for single-cell RNA sequencing: a survey.

Briefings in bioinformatics·2026
Ver todos los artículos relacionados

Video Experimental Relacionado

Updated: Jan 7, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

611

Marco espacial probabilístico basado en grafos y consciente del contexto para la eliminación de ruido interpretable y

Xianhan Qin1,2, Chang Liu1,2, Fei Gu3

  • 1School of Basic Medical Sciences, Tsinghua University, Haidian District, Beijing 100084, China.

Briefings in bioinformatics
|December 22, 2025
PubMed
Resumen
Este resumen es generado por máquina.

CadaST es un nuevo marco computacional que reduce el ruido y mejora los datos espaciales ómicos. Preserva los detalles biológicos, superando a otros métodos para el análisis de la arquitectura tisular.

Palabras clave:
eliminación de ruido de datosaprendizaje interpretablegrafo de probabilidadidentificación de dominio espacialespacial ómicagenes espacialmente variables

Más Videos Relacionados

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K

Videos de Experimentos Relacionados

Last Updated: Jan 7, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

611
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K

Área de la Ciencia:

  • Biología Computacional
  • Genómica
  • Bioinformática

Sus antecedentes:

  • Las tecnologías ómicas resueltas espacialmente proporcionan información sobre la organización tisular.
  • Los métodos analíticos actuales luchan con el ruido técnico y la preservación de la heterogeneidad biológica.

Objetivo del estudio:

  • Presentar CadaST, un marco computacional unificado e interpretable para el análisis de datos espaciales ómicos.
  • Abordar las limitaciones en el manejo del ruido técnico mientras se preserva la heterogeneidad biológica en los datos espaciales ómicos.

Principales métodos:

  • Integra la selección de características conscientes del espacio y la imputación adaptativa.
  • Infiere patrones moleculares espaciales para la eliminación de ruido y la mejora de características.
  • Emplea un enfoque centrado en el gen para evitar la sobre-suavización.

Principales resultados:

  • CadaST elimina eficazmente el ruido y aumenta los datos espaciales ómicos, preservando los límites biológicos nítidos.
  • Supera a los métodos existentes en diversas tecnologías espaciales.
  • Resuelve con precisión las capas anatómicas, caracteriza los microambientes tumorales y se escala a grandes conjuntos de datos.

Conclusiones:

  • CadaST ofrece un avance metodológico significativo para el análisis de la arquitectura tisular.
  • Proporciona una solución más precisa, interpretable y escalable para datos espaciales ómicos.
  • Permite una mejor elucidación de los principios de organización tisular en la salud y la enfermedad.