|Viktoria Dorfer studied Bioinformatics at the University of Applied Sciences Upper Austria and received her Ph.D. in informatics from the Johannes Kepler University Linz. Her research interests focus on computational proteomics, especially on peptide identification, which was also the topic of her Ph.D. thesis, entitled “Identification of Peptides and Proteins in High-resolution Tandem Mass Spectrometry Data”. Part of this thesis was the development of the MS Amanda peptide identification algorithm. At present, Vikoria is working as Professor for Bioinformatics at the University of Applied Sciences Upper Austria and is supervising two Ph.D. students and one master's student in the field of computational proteomics.
MS Amanda goes West: Integrating a Search Engine into SkylineMass spectrometry has become the method of choice for analysing proteins, demanding reliable and state-of-the-art software. Skyline has emerged as one of the most popular of these tools, supporting the generation and use of spectrum libraries from various analysis pipelines, however requiring separate pipeline execution. We present a fully integrated workflow for peptide identification and quantification within Skyline that incorporates the MS Amanda search algorithm. Read More
MS Amanda is a freely-available peptide spectrum matching algorithm, optimized for the analysis of high-resolution MS2 data. We have integrated MS Amanda into Skyline providing access to all available components in both tools. This gives researchers immediate access to a complete peptide identification and quantification pipeline inside Skyline starting directly from raw data. Finally, we expect it to apply DDA library-free DIA analysis, by running the MS Amanda search pipeline on spectra extracted from more complex and often chimeric DIA spectra using the DIA-Umpire algorithm.