2023
DOI: 10.1016/j.csbj.2023.10.006
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Metadata integrity in bioinformatics: Bridging the gap between data and knowledge

Aylin Caliskan,
Seema Dangwal,
Thomas Dandekar
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(2 citation statements)
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“…This step, as well as the additional analysis of another suitable data set, are a cost- and time-efficient preliminary step before validating the results in vitro and in vivo . Nevertheless, when analyzing big data in biomedical research, the data quality and data integrity, as well as the comprehensiveness of the metadata, can hugely affect the resulting analyses, which needs to be considered when reusing a data set or publishing a data set [ 69 ].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…This step, as well as the additional analysis of another suitable data set, are a cost- and time-efficient preliminary step before validating the results in vitro and in vivo . Nevertheless, when analyzing big data in biomedical research, the data quality and data integrity, as well as the comprehensiveness of the metadata, can hugely affect the resulting analyses, which needs to be considered when reusing a data set or publishing a data set [ 69 ].…”
Section: Discussionmentioning
confidence: 99%
“…In our showcase, we will analyze single-cell data provided by Sole ´-Boldo et al (2020) [6] (the RDS file is available via the GEO database: https://www.ncbi.nlm.nih.gov/geo/query/acc. cgi?acc=GSE130973), who analyzed human skin fibroblasts from a sun-protected area of healthy 'young' donors (25 and 27 years old) and healthy 'old' donors (53,69, and 70 years old) using single-cell RNA sequencing and found age-related changes in fibroblast subpopulations [6], using the conditions 'young' and 'old'.…”
Section: Introductionmentioning
confidence: 99%