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BioMOBS: A multi-omics visual analytics workflow for biomolecular insight generation.
Heylen, Dries; Peeters, Jannes; Aerts, Jan; Ertaylan, Gökhan; Hooyberghs, Jef.
Afiliação
  • Heylen D; Theory Lab, Data Science Institute (DSI), Hasselt University, Diepenbeek, Belgium.
  • Peeters J; Flemish Institute for Technological Research (VITO), Mol, Belgium.
  • Aerts J; Data Science Institute (DSI), Hasselt University, Diepenbeek, Belgium.
  • Ertaylan G; Visual Data Analysis Lab, Department of Biostystems KU Leuven, Leuven, Belgium.
  • Hooyberghs J; Flemish Institute for Technological Research (VITO), Mol, Belgium.
PLoS One ; 18(12): e0295361, 2023.
Article em En | MEDLINE | ID: mdl-38096184
One of the challenges in multi-omics data analysis for precision medicine is the efficient exploration of undiscovered molecular interactions in disease processes. We present BioMOBS, a workflow consisting of two data visualization tools integrated with an open-source molecular information database to perform clinically relevant analyses (https://github.com/driesheylen123/BioMOBS). We performed exploratory pathway analysis with BioMOBS and demonstrate its ability to generate relevant molecular hypotheses, by reproducing recent findings in type 2 diabetes UK biobank data. The central visualisation tool, where data-driven and literature-based findings can be integrated, is available within the github link as well. BioMOBS is a workflow that leverages information from multiple data-driven interactive analyses and visually integrates it with established pathway knowledge. The demonstrated use cases place trust in the usage of BioMOBS as a procedure to offer clinically relevant insights in disease pathway analyses on various types of omics data.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software / Diabetes Mellitus Tipo 2 Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Bélgica

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software / Diabetes Mellitus Tipo 2 Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Bélgica