The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
The Human Plasma Proteome
Open accessAbstract
We have merged four different views of the human plasma proteome, based on different methodologies, into a single nonredundant list of 1175 distinct gene products. The methodologies used were 1) literature search for proteins reported to occur in plasma or serum; 2) multidimensional chromatography of proteins followed by two-dimensional electrophoresis and mass spectroscopy (MS) identification of resolved proteins; 3) tryptic digestion and multidimensional chromatography of peptides followed by MS identification; and 4) tryptic digestion and multidimensional chromatography of peptides from low-molecular-mass plasma components followed by MS identification. Of 1,175 nonredundant gene products, 195 were included in more than one of the four input datasets. Only 46 appeared in all four. Predictions of signal sequence and transmembrane domain occurrence, as well as Genome Ontology annotation assignments, allowed characterization of the nonredundant list and comparison of the data sources. The "nonproteomic" literature (468 input proteins) is strongly biased toward signal sequence-containing extracellular proteins, while the three proteomics methods showed a much higher representation of cellular proteins, including nuclear, cytoplasmic, and kinesin complex proteins. Cytokines and protein hormones were almost completely absent from the proteomics data (presumably due to low abundance), while categories like DNA-binding proteins were almost entirely absent from the literature data (perhaps unexpected and therefore not sought). Most major categories of proteins in the human proteome are represented in plasma, with the distribution at successively deeper layers shifting from mostly extracellular to a distribution more like the whole (primarily cellular) proteome. The resulting nonredundant list confirms the presence of a number of interesting candidate marker proteins in plasma and serum.
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Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
Anderson, N. L., & Anderson, N. G. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r200007-mcp200 · Cited by 4,414
Self-citationUse of proteomic patterns in serum to identify ovarian cancer
Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07746-2 · Cited by 3,236
PROSITE: a documented database using patterns and profiles as motif descriptors
Sigrist, C. J. A. (2002) · Briefings in Bioinformatics · doi:10.1093/bib/3.3.265 · Cited by 913 · cited 1×
“Structural and Sequence-based Domain Annotation—Sequences were scanned against a library of BioPendium and iPSI-BLAST (9, 11)-like protein profiles constructed from SCOP (14), PFAM (15), PRINTS (16), and PROSITE (17) domain families.”
MethodPieper, R., Su, Q., Gatlin, C. L., Huang, S., Anderson, N. L., & Steiner, S. (2003) · PROTEOMICS · doi:10.1002/pmic.200390057 · Cited by 356
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Biomolecular coronas provide the biological identity of nanosized materials
Monopoli, M. P., Åberg, C., Salvati, A., & Dawson, K. A. (2012) · Nature Nanotechnology · doi:10.1038/nnano.2012.207 · Cited by 3,017
Nanoparticle Size and Surface Chemistry Determine Serum Protein Adsorption and Macrophage Uptake
Walkey, C. D., Olsen, J. B., Guo, H., Emili, A., & Chan, W. C. W. (2012) · Journal of the American Chemical Society · doi:10.1021/ja2084338 · Cited by 1,926
Walkey, C. D., & Chan, W. C. W. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15233e · Cited by 1,758
Absolute Quantification of Proteins by LCMSE
Silva, J. C., Gorenstein, M. V., Li, G.-Z., Vissers, J. P. C., & Geromanos, S. J. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500230-mcp200 · Cited by 1,529
Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins
Anderson, L., & Hunter, C. L. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500331-mcp200 · Cited by 1,230
Metadata
- Authors
- Anderson, N. L., Polanski, M., Pieper, R., Gatlin, T., Tirumalai, R. S., Conrads, T. P., Veenstra, T. D., Adkins, J. N., Pounds, J. G., Fagan, R., & Lobley, A.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2004-04
- Volume
- 3
- Issue
- 4
- Pages
- 311-326
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2087746647
- Cited by
- 1,006
- References
- 9
- FWCI
- 39.90
- Type
- journal article
- Language
- en
- Open access
- hybrid
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