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Computational proteomics with Jupyter and Python

Malmström, Lars LU (2019) In Methods in Molecular Biology 1977. p.237-248
Abstract

Proteomics based on mass spectrometry produces complex data in large quantities. The need for flexible computational pipelines, in the context of big data, in proteomics and other areas of science, has prompted the development of computational platforms and libraries that facilitate data analysis and data processing. In this respect, Python appears to be one of the winners among programming languages in terms of popularity and development. This chapter shows how to perform basic tasks using Python and dedicated libraries in a Jupyter framework: from basic search result summarizations to the creation of MS1 chromatograms.

Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Jupyter, JupyterHub, Proteomics, Python, R, Reproducible research
host publication
Mass Spectrometry of Proteins
series title
Methods in Molecular Biology
volume
1977
pages
12 pages
publisher
Humana Press
external identifiers
  • scopus:85064766930
  • pmid:30980332
ISSN
1064-3745
DOI
10.1007/978-1-4939-9232-4_15
language
English
LU publication?
yes
id
5e26bba0-2eff-4241-84bb-076c59d40d91
date added to LUP
2019-05-07 11:08:54
date last changed
2024-08-20 15:47:38
@inbook{5e26bba0-2eff-4241-84bb-076c59d40d91,
  abstract     = {{<p>Proteomics based on mass spectrometry produces complex data in large quantities. The need for flexible computational pipelines, in the context of big data, in proteomics and other areas of science, has prompted the development of computational platforms and libraries that facilitate data analysis and data processing. In this respect, Python appears to be one of the winners among programming languages in terms of popularity and development. This chapter shows how to perform basic tasks using Python and dedicated libraries in a Jupyter framework: from basic search result summarizations to the creation of MS1 chromatograms.</p>}},
  author       = {{Malmström, Lars}},
  booktitle    = {{Mass Spectrometry of Proteins}},
  issn         = {{1064-3745}},
  keywords     = {{Jupyter; JupyterHub; Proteomics; Python; R; Reproducible research}},
  language     = {{eng}},
  pages        = {{237--248}},
  publisher    = {{Humana Press}},
  series       = {{Methods in Molecular Biology}},
  title        = {{Computational proteomics with Jupyter and Python}},
  url          = {{http://dx.doi.org/10.1007/978-1-4939-9232-4_15}},
  doi          = {{10.1007/978-1-4939-9232-4_15}},
  volume       = {{1977}},
  year         = {{2019}},
}