Name
Title | ||
|---|---|---|
Comparison of different statistical approaches for urinary peptide biomarker detection in the context of coronary artery disease. |
Abstract | ||
|---|---|---|
In conclusion, our study revealed a very considerable dependence of peptide biomarker discovery on statistical computing of urinary peptide profiles while the observed diagnostic and/or prognostic reliability of classifiers was widely independent of the modelling approach. This may however be due to the limited statistical power in classifier testing. Nonetheless, our study showed that urinary proteome analysis has the potential to provide valuable biomarkers for coronary artery disease mirroring especially alterations in the extracellular matrix. It further showed that for a comprehensive discovery of biomarkers and thus of pathological information, the results of different statistical methods may best be combined into a master pattern that then can be used for classifier modelling. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1390-1 | BMC Bioinformatics |
Keywords | Field | DocType |
Biomarker detection,Classifier modelling,Statistical proteome analysis | Coronary artery disease,Biology,Proteomics,Biomarker (medicine),Bioinformatics,Biomarker discovery,DNA microarray,Urinary system | Journal |
Volume | Issue | ISSN |
17 | 1 | 1471-2105 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eleanor Stanley | 1 | 0 | 0.34 |
| Eleni Ioanna Delatola | 2 | 0 | 0.34 |
| Esther Nkuipou-Kenfack | 3 | 0 | 0.34 |
| William Spooner | 4 | 30 | 2.22 |
| Walter Kolch | 5 | 121 | 14.01 |
| Joost P. Schanstra | 6 | 38 | 3.45 |
| Harald Mischak | 7 | 15 | 2.31 |
| Thomas Koeck | 8 | 0 | 0.34 |