Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Data analysis techniques in phosphoproteomics

Meyer-Baese, Anke ; Wildberger, Joachim ; Meyer-Baese, Uwe and Nilsson, Carol L LU (2014) In Electrophoresis 35(24). p.62-3452
Abstract

The interpretation of phosphoproteomics data sets is crucial for generating hypotheses that guide therapeutic solutions, yet not many techniques have been applied to this type of analysis. This paper intends to give an overview about the two main standard techniques that can be applied to the analysis of these large scale data sets. These are data-driven or exploratory techniques based on a statistical model and topology-driven methods that analyze the signaling network from a dynamical standpoint. While employing different paradigms, these algorithms will detect unique "fingerprints" by revealing the intricate interactions at the proteome level and will support the experimental environment for novel therapeutics for many diseases.

Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Contribution to journal
publication status
published
keywords
Cluster Analysis, Data Interpretation, Statistical, Least-Squares Analysis, Phosphopeptides, Phosphoproteins, Principal Component Analysis, Proteomics, Support Vector Machine, Journal Article, Research Support, Non-U.S. Gov't, Review
in
Electrophoresis
volume
35
issue
24
pages
11 pages
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:25311575
  • scopus:84916625072
ISSN
0173-0835
DOI
10.1002/elps.201400219
language
English
LU publication?
no
id
d9de43b7-cc08-4687-aabb-006c77eee2dd
date added to LUP
2017-05-16 10:26:20
date last changed
2024-01-13 20:57:07
@article{d9de43b7-cc08-4687-aabb-006c77eee2dd,
  abstract     = {{<p>The interpretation of phosphoproteomics data sets is crucial for generating hypotheses that guide therapeutic solutions, yet not many techniques have been applied to this type of analysis. This paper intends to give an overview about the two main standard techniques that can be applied to the analysis of these large scale data sets. These are data-driven or exploratory techniques based on a statistical model and topology-driven methods that analyze the signaling network from a dynamical standpoint. While employing different paradigms, these algorithms will detect unique "fingerprints" by revealing the intricate interactions at the proteome level and will support the experimental environment for novel therapeutics for many diseases.</p>}},
  author       = {{Meyer-Baese, Anke and Wildberger, Joachim and Meyer-Baese, Uwe and Nilsson, Carol L}},
  issn         = {{0173-0835}},
  keywords     = {{Cluster Analysis; Data Interpretation, Statistical; Least-Squares Analysis; Phosphopeptides; Phosphoproteins; Principal Component Analysis; Proteomics; Support Vector Machine; Journal Article; Research Support, Non-U.S. Gov't; Review}},
  language     = {{eng}},
  number       = {{24}},
  pages        = {{62--3452}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Electrophoresis}},
  title        = {{Data analysis techniques in phosphoproteomics}},
  url          = {{http://dx.doi.org/10.1002/elps.201400219}},
  doi          = {{10.1002/elps.201400219}},
  volume       = {{35}},
  year         = {{2014}},
}