Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework
| Autor: | Joshua A. Klein, Mark V. Ivanov, Lev I. Levitsky, Mikhail V. Gorshkov |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Proteomics
0301 basic medicine Computer science business.industry 010401 analytical chemistry Computational Biology General Chemistry Python (programming language) computer.software_genre 01 natural sciences Biochemistry Workflow engine Workflow 0104 chemical sciences User-Computer Interface 03 medical and health sciences 030104 developmental biology Scripting language Daily practice Software engineering business computer Software computer.programming_language |
| Zdroj: | Journal of Proteome Research. 18:709-714 |
| ISSN: | 1535-3907 1535-3893 |
| Popis: | 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workflow engines; a large part of routine data processing is performed manually or with custom scripts that remain unpublished.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. |
| Databáze: | OpenAIRE |
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