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Exploration and comparison of molecular mechanisms across diseases using MINERVA Net.
Gawron, Piotr; Smula, Ewa; Schneider, Reinhard; Ostaszewski, Marek.
Afiliación
  • Gawron P; LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
  • Smula E; LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
  • Schneider R; LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
  • Ostaszewski M; LCSB, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Protein Sci ; 32(2): e4565, 2023 02.
Article en En | MEDLINE | ID: mdl-36648161
ABSTRACT
Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Biología de Sistemas Idioma: En Revista: Protein Sci Asunto de la revista: BIOQUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Luxemburgo

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Biología de Sistemas Idioma: En Revista: Protein Sci Asunto de la revista: BIOQUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Luxemburgo