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Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework
- Levitsky, Lev I., Klein, Joshua A., Ivanov, Mark V., Gorshkov, Mikhail V.
- Journal of proteome research 2018 v.18 no.2 pp. 709-714
- bioinformatics, computer software, information processing, proteome, proteomics
- Many of the novel ideas that drive today’s proteomic technologies are focused essentially on experimental or data-processing workflows. The latter are implemented and published in a number of ways, from custom scripts and programs, to projects built using general-purpose or specialized workflow engines; a large part of routine data processing is performed manually or with custom scripts that remain unpublished. Facilitating the development of reproducible data-processing workflows becomes essential for increasing the efficiency of proteomic research. To assist in overcoming the bioinformatics challenges in the daily practice of proteomic laboratories, 5 years ago we developed and announced Pyteomics, a freely available open-source library providing Python interfaces to proteomic data. We summarize the new functionality of Pyteomics developed during the time since its introduction.