6533b858fe1ef96bd12b5a2e
RESEARCH PRODUCT
A Approach to Clinical Proteomics Data Quality Control and Import
Pierre NaubourgKokou YetongnonMarinette SavonnetEric Leclercqsubject
Process (engineering)Computer sciencemedia_common.quotation_subject02 engineering and technologyOntology (information science)Proteomicscomputer.software_genreDomain (software engineering)03 medical and health sciences020204 information systems[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM]0202 electrical engineering electronic engineering information engineeringInformation systemQuality (business)[ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]030304 developmental biologymedia_common0303 health sciences[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]Data science[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Data qualityData mining[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]computerdescription
International audience; Biomedical domain and proteomics in particular are faced with an increasing volume of data. The heterogeneity of data sources implies heterogeneity in the representation and in the content of data. Data may also be incorrect, implicate errors and can compromise the analysis of experiments results. Our approach aims to ensure the initial quality of data during import into an information system dedicated to proteomics. It is based on the joint use of models, which represent the system sources, and ontologies, which are use as mediators between them. The controls, we propose, ensure the validity of values, semantics and data consistency during import process.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2011-08-29 |