Knowledge management for systems biology a general and visually driven framework applied to translational medicine
Autor/a
Maier, Dieter
Kalus, Wenzel
Wolff, Martin
Kalko, Susana G.
Roca, Josep
Marin de Mas, Igor
Turan, Nil
Cascante, Marta
Falciani, Francesco
Hernandez, Miguel
Losko, Sascha
Data de publicació
2011ISSN
1752-0509
Resum
Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.
Tipus de document
Article
Versió del document
Versió publicada
Llengua
English
Matèries (CDU)
61 - Medicina
Paraules clau
Malalties cròniques
Pulmons -- Malalties obstructives
Gestió del coneixement
Biologia sintètica
Enfermedades crónicas
Enfermedad pulmonar obstructiva crónica
Gestión del conocimiento
Biología sintética
Chronic diseases
Lungs -- Diseases
Knowledge management
Synthetic biology
Pàgines
16
Publicat per
BMC Systems Biology
Col·lecció
5;
Publicat a
BMC Systems Biology
Citació
Maier, Dieter; Kalus, Wenzel; Wolff, Martin [et al.]. Knowledge management for systems biology a general and visually driven framework applied to translational medicine. BMC Systems Biology, 2011, 5, p. 1-16. Disponible en: <https://bmcsystbiol.biomedcentral.com/articles/10.1186/1752-0509-5-38>. Fecha de acceso: 28 oct. 2020. DOI: 10.1186/1752-0509-5-38
Aquest element apareix en la col·lecció o col·leccions següent(s)
- Ciències de la Salut [740]
Drets
© 2011 Maier et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Excepte que s'indiqui una altra cosa, la llicència de l'ítem es descriu com https://creativecommons.org/licenses/by/2.0/