RT Journal Article
T1 S2P: A software tool to quickly carry out reproducible biomedical research projects involving 2D-gel and MALDI-TOF MS protein data
A1 López Fernández, Hugo
A1 Araújo, José E
A1 Jorge, Susana
A1 González Peña, Daniel
A1 Reboiro Jato, Miguel
A1 Carreira dos Santos, Hugo Miguel Baptista
A1 Fernández Riverola, Florentino
A1 Capelo Martínez, José Luis
K1 2301 Química Analítica
K1 1203.17 Informática
AB Background and objective  2D-gel electrophoresis is widely used in combination with MALDI-TOF mass spectrometry in order to analyze the proteome of biological samples. For instance, it can be used to discover proteins that are differentially expressed between two groups (e.g. two disease conditions, case vs. control, etc.) thus obtaining a set of potential biomarkers. This procedure requires a great deal of data processing in order to prepare data for analysis or to merge and integrate data from different sources. This kind of work is usually done manually (e.g. copying and pasting data into spreadsheet files), which is highly time consuming and distracts the researcher from other important, core tasks. Moreover, engaging in a repetitive process in a non-automated, handling-based manner is prone to error, thus threatening reliability and reproducibility. The objective of this paper is to present S2P, an open source software to overcome these drawbacks.   Methods  S2P is implemented in Java on top of the AIBench framework, and relies on well-established open source libraries to accomplish different tasks.   Results  S2P is an AIBench based desktop multiplatform application, specifically aimed to process 2D-gel and MALDI-mass spectrometry protein identification-based data in a computer-aided, reproducible manner. Different case studies are presented in order to show the usefulness of S2P.   Conclusions  S2P is open source and free to all users at http://www.sing-group.org/s2p. Through its user-friendly GUI interface, S2P dramatically reduces the time that researchers need to invest in order to prepare data for analysis.
PB Computer Methods and Programs in Biomedicine
SN 01692607
YR 2018
FD 2018-03
LK http://hdl.handle.net/11093/5546
UL http://hdl.handle.net/11093/5546
LA eng
NO Computer Methods and Programs in Biomedicine, 155, 1-9 (2018)
NO Ministerio de Economía y Competitividad | Ref. TIN2013-47153-C3-3-R
DS Investigo
RD 13-ene-2025