Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics
Publication type: Journal Article
Publication date: 2013-01-05
scimago Q1
wos Q1
SJR: 0.704
CiteScore: 5.0
Impact factor: 2.7
ISSN: 10440305, 18791123
PubMed ID:
23292976
Spectroscopy
Structural Biology
Abstract
Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python.org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com.
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Metrics
189
Total citations:
189
Citations from 2024:
44
(23%)
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GOST
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Goloborodko A. et al. Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics // Journal of the American Society for Mass Spectrometry. 2013. Vol. 24. No. 2. pp. 301-304.
GOST all authors (up to 50)
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Goloborodko A., Levitsky L., Ivanov M., Gorshkov M. V. Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics // Journal of the American Society for Mass Spectrometry. 2013. Vol. 24. No. 2. pp. 301-304.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1007/s13361-012-0516-6
UR - https://doi.org/10.1007/s13361-012-0516-6
TI - Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics
T2 - Journal of the American Society for Mass Spectrometry
AU - Goloborodko, Anton
AU - Levitsky, Lev
AU - Ivanov, Mark
AU - Gorshkov, Mikhail V.
PY - 2013
DA - 2013/01/05
PB - American Chemical Society (ACS)
SP - 301-304
IS - 2
VL - 24
PMID - 23292976
SN - 1044-0305
SN - 1879-1123
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2013_Goloborodko,
author = {Anton Goloborodko and Lev Levitsky and Mark Ivanov and Mikhail V. Gorshkov},
title = {Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics},
journal = {Journal of the American Society for Mass Spectrometry},
year = {2013},
volume = {24},
publisher = {American Chemical Society (ACS)},
month = {jan},
url = {https://doi.org/10.1007/s13361-012-0516-6},
number = {2},
pages = {301--304},
doi = {10.1007/s13361-012-0516-6}
}
Cite this
MLA
Copy
Goloborodko, Anton, et al. “Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics.” Journal of the American Society for Mass Spectrometry, vol. 24, no. 2, Jan. 2013, pp. 301-304. https://doi.org/10.1007/s13361-012-0516-6.
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