The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0
Open accessAbstract
PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for the analysis of shotgun proteomic data. The contained modules allow for formatting of sequence databases, peptide spectrum matching, statistical filtering and data organization, extracting quantitative information from label-free and chemically labeled data, and analyzing statistics for differential proteomics. PatternLab also has modules to perform similarity-driven studies with de novo sequencing data, to evaluate time-course experiments and to highlight the biological significance of data with regard to the Gene Ontology database. The PatternLab for proteomics 4.0 package brings together all of these modules in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats. All updates to PatternLab, including new features, have been previously tested on millions of mass spectra. PatternLab is easy to install, and it is freely available from http://patternlabforproteomics.org.
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Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Beausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P. (2006) · Nature Biotechnology · doi:10.1038/nbt1240 · Cited by 1,577
Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions
Picotti, P., & Aebersold, R. (2012) · Nature Methods · doi:10.1038/nmeth.2015 · Cited by 1,302
McAlister, G. C., Nusinow, D. P., Jedrychowski, M. P., Wühr, M., Huttlin, E. L., Erickson, B. K., Rad, R., Haas, W., & Gygi, S. P. (2014) · Analytical Chemistry · doi:10.1021/ac502040v · Cited by 1,263
Hebert, A. S., Richards, A. L., Bailey, D. J., Ulbrich, A., Coughlin, E. E., Westphall, M. S., & Coon, J. J. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.034769 · Cited by 528 · cited 1×
“Shotgun proteomics has revolutionized biochemical and bio-medical research by enabling the identification and quantification of thousands of proteins in complex biological samples such as organelles, cell lysates, biological fluids and tissues 1 .”
BackgroundDeutsch, E. W., Mendoza, L., Shteynberg, D., Slagel, J., Sun, Z., & Moritz, R. L. (2015) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201400164 · Cited by 342
Cited by
Caldwell, A. L. M., Sancho, L., Deng, J., Bosworth, A., Miglietta, A., Diedrich, J. K., Shokhirev, M. N., & Allen, N. J. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01150-1 · Cited by 86
Altered Carbon Partitioning Enhances CO2 to Terpene Conversion in Cyanobacteria
Li, M., Long, B., Dai, S. Y., Golden, J. W., Wang, X., & Yuan, J. S. (2022) · BioDesign Research · doi:10.34133/2022/9897425 · Cited by 20
Borges, R. J., Salvador, G. H. M., Pimenta, D. C., dos Santos, L. D., Fontes, M. R. M., & Usón, I. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac029 · Cited by 5
Metadata
- Authors
- Carvalho, P. C., Lima, D. B., Leprevost, F. V., Santos, M. D. M., Fischer, J. S. G., Aquino, P. F., Moresco, J. J., Yates, J. R., & Barbosa, V. C.
- Venue
- Nature Protocols
- Published
- 2015-12-10
- Volume
- 11
- Issue
- 1
- Pages
- 102-117
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- OpenAlex
- W2196345157
- Cited by
- 283
- References
- 8
- FWCI
- 7.78
- Type
- journal article
- Language
- en
- Open access
- bronze
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