期刊
BIOINFORMATICS
卷 25, 期 8, 页码 1076-1077出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btp094
关键词
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When feature selection in mass spectrometry is based on single m/z values, problems arise from the fact that variability is not only in vertical but also in horizontal direction, i.e. also slightly differing m/z values may correspond to the same feature. Hence, we propose to use the full spectra as input to a classifier, but to select small groups - or blocks - of adjacent m/z values, instead of single m/z values only. For that purpose we modify the LogitBoost to obtain a version of the so-called blockwise boosting procedure for classification. It is shown that blockwise boosting has high potential in predictive proteomics.
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