Proteomics reading list

Note: this reading list accompanies the blog article, Have you read these 21 must-read proteomics articles?.

  1. Bereman M.S. (2014). “Tools for Monitoring Systems Suitability in LC MS/MS Centric Proteomic Experiments”. Accepted article in Proteomics (DOI: 10.1002/pmic.201400373). [Subscription required]
  2. Wang X., Chambers M.C., Vega-Montoto L.J. et al. (2014). “QC Metrics from CPTAC Raw LC-MS/MS Data Interpreted through Multivariate Statistics”. Anal Chem 86 (5), 2497-509. [Subscription required]
  3. Amidan B.G., Orton D.J., LaMarche B.L et al. (2014). “Signatures for Mass Spectrometry Data Quality”. J Proteome Res 13 (4), 2215-22. [Subscription required]
  4. Ternent T., Csordas A., Qi D. et al. (2014). “How to submit MS proteomics data to ProteomeXchange via the PRIDE database”. Proteomics 14 (20), 2233-41. [Open access]
  5. Vizcaíno J.A., Deutsch E.W., Wang R. et al. (2014). “ProteomeXchange provides globally coordinated proteomics data submission and dissemination”. Nature Biotechnology 32, 223-6. [Open access]
  6. Römpp A., Wang R., Albar, J.P. et al. (2014). “A public repository for mass spectrometry imaging data”. Anal Bioanal Chem, DOI 10.1007/s00216-014-8357-8 [Open access]
  7. Perez-Riverol Y., Alpi E., Wang R. et al. (2014). “Making proteomics data accessible and reusable: Current state of proteomics databases and repositories”. Accepted article in Proteomics (DOI: 10.1002/pmic.201400302). [Open access]
  8. Deutsch E.W. (2010). “File formats commonly used in mass spectrometry proteomics.” Mol Cell Proteomics 11 (12), 1612-21. [Open access]
  9. Martens L., Chambers M., Sturm M. et al. (2011). “mzML—a Community Standard for Mass Spectrometry Data”. Mol Cell Proteomics 10 (1), R110.000133. [Open access]
  10. Jones A.R., Eisenacher M., Mayer G. et al. (2012). “The mzIdentML Data Standard for Mass Spectrometry-Based Proteomics Results”. Mol Cell Proteomics 11 (7), M111.014381. [Open access]
  11. Walzer M., Qi D., Mayer G. et al. (2013). “The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics”. Mol Cell Proteomics 12 (8), 2332-40. [Open access]
  12. Walzer M., Espona Pernas L., Nasso S. et al. (2014). “qcML: An Exchange Format for Quality Control Metrics from Mass Spectrometry Experiments”. Mol Cell Proteomics 13 (8), 1905-13. [Open access]
  13. Karp N.A. and Lilley K.S. (2007). “Design and analysis issues in quantitative proteomics studies.” Proteomics (Volume 7, Supplement: Practical Proteomics Issue 1), 42-50. [Subscription required]
  14. Ioannidis, J.P.A. (2005). “Why Most Published Research Findings Are False”. PLoS Med 2 (8), e124. [Open access]
  15. Micheel C.M., Nass S.J and Omenn, G.S. (Eds) (2012). “Evolution of Translational Omics: Lessons Learned and the Path Forward”. Committee on the Review of Omics-Based Tests for Predicting Patient Outcomes in Clinical Trials; Board on Health Care Services; Board on Health Sciences Policy; Institute of Medicine. Washington (DC): National Academies Press (US).  [Open access]
  16. Karpievitch Y.V., Dabney A.R., and Smith R.D. (2012). “Normalization and missing value imputation for label-free LC-MS analysis”. BMC Bioinformatics 13 (S5). [Open access]
  17. Nesvizhskii A.I. (2010). “A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics”. J Proteomics 73 (11), 2092-123. [Open access]
  18. Law K.P. and Lim Y.P. (2013). “Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring”. Expert Rev Proteomics 10 (6), 551-66. [Subscription required]
  19. Sajic T., Liu Y. and Aebersold R. (2014). “Using Data-Independent, High Resolution Mass Spectrometry in Protein Biomarker Research: Perspectives and Clinical Applications”. Accepted article in Proteomics: Clinical Applications (DOI: 10.1002/prca.201400117). [Subscription required]
  20. Nesvizhskii A.I. and Aebersold R. (2005). “Interpretation of Shotgun Proteomic Data: The Protein Inference Problem”. Mol Cell Proteomics 4 (10), 1419-40. [Open access]
  21. Li Y.F. and Radivojac P. (2012). “Computational approaches to protein inference in shotgun proteomics”. BMC Bioinformatics 13 (Suppl 16), S4. [Open access]