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Nonribosomal peptides (NRPs) are of great pharmacological importance, but there is currently no technology for high-throughput NRP 'dereplication' and sequencing. We used multistage mass spectrometry followed by spectral alignment algorithms for sequencing of cyclic NRPs. We also developed an algorithm for comparative NRP dereplication that establishes(More)
Empirical results are presented concerning data fusion performed over several combinations of EEG/ECG channel readings of sport shooting athletes. Our purpose in applying different data fusion approaches was that of finding a satisfactory set of features, such that would allow us to build adequate classifiers on the data. The resulting data sets were used(More)
Diverse neuropeptides participate in cell-cell communication to coordinate neuronal and endocrine regulation of physiological processes in health and disease. Neuropeptides are short peptides ranging in length from ~3 to 40 amino acid residues that are involved in biological functions of pain, stress, obesity, hypertension, mental disorders, cancer, and(More)
Tandem mass spectrometry (MS/MS) experiments often generate redundant data sets containing multiple spectra of the same peptides. Clustering of MS/MS spectra takes advantage of this redundancy by identifying multiple spectra of the same peptide and replacing them with a single representative spectrum. Analyzing only representative spectra results in(More)
Through elaboration of its botulinum toxins, Clostridium botulinum produces clinical syndromes of infant botulism, wound botulism, and other invasive infections. Using comparative genomic analysis, an orphan nine-gene cluster was identified in C. botulinum and the related foodborne pathogen Clostridium sporogenes that resembled the biosynthetic machinery(More)
Database search tools identify peptides by matching tandem mass spectra against a protein database. We study an alternative approach when all plausible de novo interpretations of a spectrum (spectral dictionary) are generated and then quickly matched against the database. We present a new MS-Dictionary algorithm for efficiently generating spectral(More)
Despite significant advances in the identification of known proteins, the analysis of unknown proteins by MS/MS still remains a challenging open problem. Although Klaus Biemann recognized the potential of MS/MS for sequencing of unknown proteins in the 1980s, low throughput Edman degradation followed by cloning still remains the main method to sequence(More)
Automated database search engines are one of the fundamental engines of high-throughput proteomics enabling daily identifications of hundreds of thousands of peptides and proteins from tandem mass (MS/MS) spectrometry data. Nevertheless, this automation also makes it humanly impossible to manually validate the vast lists of resulting identifications from(More)