| Title: |
Towards standardization guidelines for in silico approaches in personalized medicine |
| Authors: |
Brunak Søren, Bjerre Collin Catherine, Eva Ó Cathaoir Katharina, Golebiewski Martin, Kirschner Marc, Kockum Ingrid, Moser Heike, Waltemath Dagmar |
| Source: |
Journal of Integrative Bioinformatics, Vol 17, Iss 2-3, Pp 21-106 (2020) |
| Publisher Information: |
De Gruyter, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Biotechnology |
| Subject Terms: |
data integration, in silico modelling, personalized medicine, reproducibility, standards, Biotechnology, TP248.13-248.65 |
| More Details: |
Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1613-4516 |
| Relation: |
https://doaj.org/toc/1613-4516 |
| DOI: |
10.1515/jib-2020-0006 |
| Access URL: |
https://doaj.org/article/f85172b9cf2f4dfda8aecc54768d57fe |
| Accession Number: |
edsdoj.f85172b9cf2f4dfda8aecc54768d57fe |
| Database: |
Directory of Open Access Journals |
