Heteromer score-using internal standards to assess the quality of proteomic data

Proteomics

Volumn 14, Issue 9, 2014, Pages 1042-1047

  Rogowska Wrzesinska, Adelina ^a   Wrzesinski, Krzysztof ^a   Fey, Stephen J ^a  

^a UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

Author keywords

Bioinformatics; Cell biology; Heterodimer; Heteromer score; Internal standard; Quality control

Indexed keywords

HEMOGLOBIN; HETERODIMER; HOMODIMER; PROTEIN;

ARTICLE; BIOINFORMATICS; CELL CULTURE; CELL LINE; CORRELATION COEFFICIENT; DATA ANALYSIS; HETEROMER SCORE; HUMAN; LIPID DIET; LIVER CELL; LIVER MITOCHONDRION; LUNG ADENOCARCINOMA; MASS SPECTROMETER; MICROTUBULE; NONHUMAN; NUCLEOSOME; OXIDATIVE PHOSPHORYLATION; PRIORITY JOURNAL; PROTEIN EXPRESSION; PROTEIN SUBUNIT; PROTEOMICS; QUALITY CONTROL; RESPIRATORY CHAIN; STANDARD; STOICHIOMETRY; PROTEIN DATABASE; REPRODUCIBILITY; STANDARDS;

DATABASES, PROTEIN; PROTEINS; PROTEOMICS; REFERENCE STANDARDS; REPRODUCIBILITY OF RESULTS;

EID: 84898607302     PISSN: 16159853     EISSN: 16159861     Source Type: Journal    
DOI: 10.1002/pmic.201300457     Document Type: Article

References (14)

1. Ong, S. E., Mann, M., Mass spectrometry-based proteomics turns quantitative. Nat. Chem. Biol. 2005, 1, 252-262.
2. Bantscheff, M., Schirle, M., Sweetman, G., Rick, J., Kuster, B., Quantitative mass spectrometry in proteomics: a critical review. Anal. Bioanal. Chem. 2007, 389, 1017-1031.
3. Cappadona, S., Baker, P. R., Cutillas, P. R., Heck, A. J., van Breukelen, B., Current challenges in software solutions for mass spectrometry-based quantitative proteomics. Amino Acids 2012, 43, 1087-1108.
4. Martinez-Bartolome, S., Deutsch, E. W., Binz, P. A., Jones, A. R. et al., Guidelines for reporting quantitative mass spectrometry based experiments in proteomics. J. Proteomics 2013, 95, 84-88.
5. Boersema, P. J., Raijmakers, R., Lemeer, S., Mohammed, S., Heck, A. J., Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat/Protoc. 2009, 4, 484-494.
6. Wisniewski, J. R., Ostasiewicz, P., Dus, K., Zielinska, D. F. et al., Extensive quantitative remodeling of the proteome between normal colon tissue and adenocarcinoma. Mol. Syst. Biol. 2012, 8, 611-626.
7. Luber, C. A., Cox, J., Lauterbach, H., Fancke, B. et al., Quantitative proteomics reveals subset-specific viral recognition in dendritic cells. Immunity 2010, 32, 279-289.
8. Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B. et al., Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 2002, 1, 376-386.
9. Zanivan, S., Maione, F., Hein, M. Y., Hernandez-Fernaud, J. R. et al., SILAC-based proteomics of human primary endothelial cell morphogenesis unveils tumor angiogenic markers. Mol. Cell. Proteomics 2013, 12, 3599-3611.
10. Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B. et al., Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics 2004, 3, 1154-1169.
11. Rowe, C., Gerrard, D. T., Jenkins, R., Berry, A. et al., Proteome-wide analyses of human hepatocytes during differentiation and dedifferentiation. Hepatology 2013, 58, 799-809.
12. Pernemalm, M., De Petris, L., Branca, R. M., Forshed, J. et al., Quantitative proteomics profiling of primary lung adenocarcinoma tumors reveals functional perturbations in tumor metabolism. J. Proteome Res. 2013, 12, 3934-3943.
13. Wrzesinski, K., León, I. R., Kulej, K., Sprenger, R. R. et al., Proteomics identifies molecular networks affected by tetradecylthioacetic acid and fish oil supplemented diets. J. Proteomics 2013, 84, 61-77.
14. Berry, E. A., De Bari, H., Huang, L. S., Unanswered questions about the structure of cytochrome bc1 complexes. Biochim. Biophys. Acta 2013, 1827, 1258-1277.