most citedSparse Proteomics Analysis - A compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

25 citations · 25 across the 1 of their papers we have counts for

collaborators

1 paper

math.ST2015★ 25 cited

Sparse Proteomics Analysis - A compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

Tim Conrad, Martin Genzel, Nada Cvetkovic +5

Background: High-throughput proteomics techniques, such as mass spectrometry (MS)-based approaches, produce very high-dimensional data-sets. In a clinical setting one is often inte…