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Laboratory data and sample management for proteomics.

Häkkinen, Jari LU orcid and Levander, Fredrik LU (2011) In Methods in Molecular Biology 696. p.79-92
Abstract
Proteomic experiments can be difficult to handle because of the large amount of data in different formats that is generated. Samples need to be managed and generated, data needs to be integrated with samples and annotation information. A laboratory information management system (LIMS) can be used to overcome some of the data handling problems. In this chapter, we discuss the role of a LIMS in the proteomics laboratory, and show two step-by-step examples of usage of the Proteios Software Environment (ProSE) to handle two different proteomics workflows.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Data Mining in Proteomics : From Standards to Applications
series title
Methods in Molecular Biology
editor
Hamacher, Michael ; Eisenacher, Martin and Stephan, Christian
volume
696
pages
79 - 92
publisher
Springer
external identifiers
  • pmid:21063942
  • scopus:79952201416
  • pmid:21063942
ISSN
1940-6029
ISBN
978-1-60761-986-4
DOI
10.1007/978-1-60761-987-1_5
language
English
LU publication?
yes
id
627b4ec1-6776-4616-b3f2-9b0f4d6e52e1 (old id 1732109)
date added to LUP
2016-04-04 08:05:15
date last changed
2022-05-15 20:01:37
@inbook{627b4ec1-6776-4616-b3f2-9b0f4d6e52e1,
  abstract     = {{Proteomic experiments can be difficult to handle because of the large amount of data in different formats that is generated. Samples need to be managed and generated, data needs to be integrated with samples and annotation information. A laboratory information management system (LIMS) can be used to overcome some of the data handling problems. In this chapter, we discuss the role of a LIMS in the proteomics laboratory, and show two step-by-step examples of usage of the Proteios Software Environment (ProSE) to handle two different proteomics workflows.}},
  author       = {{Häkkinen, Jari and Levander, Fredrik}},
  booktitle    = {{Data Mining in Proteomics : From Standards to Applications}},
  editor       = {{Hamacher, Michael and Eisenacher, Martin and Stephan, Christian}},
  isbn         = {{978-1-60761-986-4}},
  issn         = {{1940-6029}},
  language     = {{eng}},
  pages        = {{79--92}},
  publisher    = {{Springer}},
  series       = {{Methods in Molecular Biology}},
  title        = {{Laboratory data and sample management for proteomics.}},
  url          = {{http://dx.doi.org/10.1007/978-1-60761-987-1_5}},
  doi          = {{10.1007/978-1-60761-987-1_5}},
  volume       = {{696}},
  year         = {{2011}},
}