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Spatial molecular profiling: platforms, applications and analysis tools.
Zhang, Minzhe; Sheffield, Thomas; Zhan, Xiaowei; Li, Qiwei; Yang, Donghan M; Wang, Yunguan; Wang, Shidan; Xie, Yang; Wang, Tao; Xiao, Guanghua.
Afiliación
  • Zhang M; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Sheffield T; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Zhan X; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Li Q; Department of Mathematics Sciences at University of Texas at Dallas.
  • Yang DM; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Wang Y; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Wang S; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Xie Y; Quantitative Biomedical Research Center at the University of Texas Southwestern Medical Center.
  • Wang T; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
  • Xiao G; Department of Population and Data Sciences at University of Texas Southwestern Medical Center.
Brief Bioinform ; 22(3)2021 05 20.
Article en En | MEDLINE | ID: mdl-32770205
Molecular profiling technologies, such as genome sequencing and proteomics, have transformed biomedical research, but most such technologies require tissue dissociation, which leads to loss of tissue morphology and spatial information. Recent developments in spatial molecular profiling technologies have enabled the comprehensive molecular characterization of cells while keeping their spatial and morphological contexts intact. Molecular profiling data generate deep characterizations of the genetic, transcriptional and proteomic events of cells, while tissue images capture the spatial locations, organizations and interactions of the cells together with their morphology features. These data, together with cell and tissue imaging data, provide unprecedented opportunities to study tissue heterogeneity and cell spatial organization. This review aims to provide an overview of these recent developments in spatial molecular profiling technologies and the corresponding computational methods developed for analyzing such data.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Bases de Datos Factuales / Perfilación de la Expresión Génica / Genómica Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Bases de Datos Factuales / Perfilación de la Expresión Génica / Genómica Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article