This review “teaches” researchers how to make their lackluster proteomics data look really
impressive, by applying an inappropriate but pervasive strategy that selects features in a …

To build a credible model for given chemical or biological or clinical data, it may be helpful to
first get somewhat better insight into the data itself before modeling and then to present the …

Background Mass spectrometry is one of the most important techniques in the field of
proteomics. MALDI-TOF mass spectrometry has become popular during the last decade due …

The fields of proteomics and machine learning are both large disciplines, each producing
well over 5,000 publications per year. However, studies combining both fields are still …

Background: Due to its prevalence and negative impacts on both the economy and society,
the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label …

Microorganism identification by MALDI TOF mass-spectrometry is based on the comparison
of the mass spectrum of the studied organism with those of reference strains. It is a rapid and …

Machine learning techniques can be applied to MALDI-TOF mass spectral data of drug-
treated cells to obtain classification models which assign the mechanism of action of drugs …

The advent of high-throughput next generation sequencing technologies have fostered
enormous potential applications of supercomputing techniques in genome sequencing, epi …

Peak picking is an early key step in MS data analysis. We compare three commonly used
approaches to peak picking and discuss their merits by means of statistical analysis …

In this work, we analyze and evaluate different strategies for comparing Feature Selection
(FS) schemes on High Dimensional (HD) biomedical datasets (eg gene and protein …