Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik

Permanent URI for this collectionhttps://hdl.handle.net/11147/9

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Subject: search.filters.subject.ProteomicsWoS Q: search.filters.wosQuartile.N/A

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  • Letter
    Citation - Scopus: 9
    A Call for Benchmark Data in Mass Spectrometry-Based Proteomics
    (Proteomass Scientific Society, 2012) Allmer, Jens
    Proteomics is a quickly developing field. New and better mass spectrometers, the platform of choice in proteomics, are being introduced frequently. New algorithms for the analysis of mass spectrometric data and assignment of amino acid sequence to tandem mass spectra are also presented on a frequent basis. Unfortunately, the best application area for these algorithms cannot be established at the moment. Furthermore, even the accuracy of the algorithms and their relative performance cannot be established. This is due to the lack of proper benchmark data. This letter first introduces the field of mass spectrometry-based proteomics and then defines the expectations of a well-designed benchmark dataset. Thereafter, the current situation is compared to this ideal. A call for the creation of a proper benchmark dataset is then placed and it is explained how measurement should be performed. Finally, the benefits for the research community are highlighted. © 2012, Proteomass Scientific Society. All rights reserved.
  • Conference Object
    Citation - Scopus: 1
    De Novo Markup Language, a Standard To Represent De Novo Sequencing Results From Ms/Ms Data
    (Institute of Electrical and Electronics Engineers Inc., 2012) Takan, Savaş; Allmer, Jens
    Proteomics is the study of the proteins that can be derived from a genome. For the identification and sequencing of proteins, mass spectrometry has become the tool of choice. Within mass spectrometry-based proteomics, proteins can be identified or sequenced by either database search or de novo sequencing. Both methods have certain advantages and drawbacks but in the long run we envision de novo sequencing to become the predominant tool. Currently, de novo sequencing results are stored in arbitrary file formats, depending on the developers of the algorithms. We identified this as a large and unnecessary obstacle while integrating results from multiple de novo sequencing algorithms. Therefore, we designed a standard file format for the representation of de novo sequencing results. We further developed an application programming interface since we identified the lack of proper APIs as another obstacle, introducing a needlessly high learning curve for developers. © 2012 IEEE.