The use of proteomic and bioinformatics techniques for the detection of protein biomarkers following growth hormone administration
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Boateng, J. 
ORCID: https://orcid.org/0000-0002-6310-729X, Lancashire, L., Brown, P., Ahmad, M., Ball, B., Davy, R., Yu Yang, S., Roberts, J., Teale, P., Velloso, C., Rees, R., Ball, G., Goldspink, G. and Creaser, C.
(2007)
The use of proteomic and bioinformatics techniques for the detection of protein biomarkers following growth hormone administration.
The Internet Journal of Genomics and Proteomics, 2 (2).
ISSN 1540-2630
(doi:10.5580/c79)
Abstract
A combined mass spectrometry and bioinformatics screening technique has been developed for detecting the administration of exogenous growth hormone (GH), through changes in the serum proteome. Serum samples from porcine GH (n=14) and placebo (n=13) treated mice were analysed by MALDI-TOF-MS. Mass spectrometric data were processed using artificial neural networks to identify protein biomarkers capable of differentiating between control and GH treated subjects. Four ions m/z 17201 (± 34), 18978 (± 38), 19860 (± 40) and 20190 (± 40) were identified, which correctly predicted 93 % of a separate subset of blind samples. The sensitivity and specificity of the model was respectively 86 % and 100 % (12/14 GH treated and 13/13 controls correctly assigned respectively). Reproducibility of the four ion model was assessed using an intra-laboratory replicate data set of separately prepared serum samples. Our results show the potential of MALDI-MS for detecting GH administration with good sensitivity and specificity through indicative biomarker patterns determined using computational bioinformatics techniques.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial neural network, growth hormone administration, High throughput screening, MALDI/MS, serum protein biomarkers |
| Subjects: | Q Science > QR Microbiology |
| Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science > School of Science (SCI) |
| Related URLs: | |
| Last Modified: | 09 Dec 2016 14:29 |
| URI: | http://gala.gre.ac.uk/id/eprint/8274 |
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