TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Horsch, Salome
A1  - Kopczynski, Dominik
A1  - Kuthe, Elias
A1  - Baumbach, Jörg
A1  - Rahmann, Sven
A1  - Rahnenführer, Jörg
T1  - A detailed comparison of analysis processes for MCC-IMS data in disease classification - automated methods can replace manual peak annotations
JF  - PLOS ONE
N2  - The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology.
Y1  - 2017
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-14870
U6  - https://doi.org/10.1371/journal.pone.0184321
DO  - https://doi.org/10.1371/journal.pone.0184321
VL  - 12
IS  - 9
SP  - 1
EP  - 16
S1  - 16
PB  - PLOS
CY  - Lawrence, Kan.
ER  -