Projects per year
Results: The magnitude of missingness did not correlate with mean peptide concentration. The magnitude of missingness for each protein strongly correlated between collection time points (baseline, 3 months, 6 months; R = 0.95-0.97, CI = 0.94, 0.97) indicating little time-dependent effect. This allowed for the identification of proteins with outlier levels of missingness that differenti-ate between patient groups characterized by different patterns of disease activity. The association of these proteins with disease activity was confirmed by machine learning techniques.
Conclusion: Our novel approach complements analyses on complete observations and other missing value strategies in biomarker prediction of disease activity.
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- 1 Finished
Manchester Molecular Pathology Innovation Centre (MMPathIC): Bridging the Gap Between Biomarker Discovery and Health and Wealth.
1/10/15 → 31/03/21