BMC Bioinformatics | |
Mass-Up: an all-in-one open software application for MALDI-TOF mass spectrometry knowledge discovery | |
Software | |
H. M. Santos1  J. L. Capelo1  D. Glez-Peña2  H. López-Fernández2  M. Reboiro-Jato2  F. Fdez-Riverola2  | |
[1] BIOSCOPE Research Group, UCIBIO-REQUIMTE, Department of Chemistry, Faculty of Science and Technology, Universidade NOVA de Lisboa, Caparica, Setubal, Portugal;Informatics Department, Universidad de Vigo, Campus Universitario As Lagoas s/n, 32004, Ourense, Spain;Instituto de Investigación Biomédica de Vigo (IBIV), Vigo, Pontevedra, Spain; | |
关键词: Mass spectrometry; MALDI-TOF-MS; Knowledge discovery; Machine learning; Biomarker discovery; | |
DOI : 10.1186/s12859-015-0752-4 | |
received in 2015-05-06, accepted in 2015-09-28, 发布年份 2015 | |
来源: Springer | |
【 摘 要 】
BackgroundMass spectrometry is one of the most important techniques in the field of proteomics. MALDI-TOF mass spectrometry has become popular during the last decade due to its high speed and sensitivity for detecting proteins and peptides. MALDI-TOF-MS can be also used in combination with Machine Learning techniques and statistical methods for knowledge discovery. Although there are many software libraries and tools that can be combined for these kind of analysis, there is still a need for all-in-one solutions with graphical user-friendly interfaces and avoiding the need of programming skills.ResultsMass-Up, an open software multiplatform application for MALDI-TOF-MS knowledge discovery is herein presented. Mass-Up software allows data preprocessing, as well as subsequent analysis including (i) biomarker discovery, (ii) clustering, (iii) biclustering, (iv) three-dimensional PCA visualization and (v) classification of large sets of spectra data.ConclusionsMass-Up brings knowledge discovery within reach of MALDI-TOF-MS researchers. Mass-Up is distributed under license GPLv3 and it is open and free to all users at http://sing.ei.uvigo.es/mass-up.
【 授权许可】
CC BY
© López-Fernández et al. 2015
【 预 览 】
Files | Size | Format | View |
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RO202311104172100ZK.pdf | 3762KB | download |
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