The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
PrognoScan: a new database for meta-analysis of the prognostic value of genes
Open accessAbstract
BACKGROUND: In cancer research, the association between a gene and clinical outcome suggests the underlying etiology of the disease and consequently can motivate further studies. The recent availability of published cancer microarray datasets with clinical annotation provides the opportunity for linking gene expression to prognosis. However, the data are not easy to access and analyze without an effective analysis platform. DESCRIPTION: To take advantage of public resources in full, a database named "PrognoScan" has been developed. This is 1) a large collection of publicly available cancer microarray datasets with clinical annotation, as well as 2) a tool for assessing the biological relationship between gene expression and prognosis. PrognoScan employs the minimum P-value approach for grouping patients for survival analysis that finds the optimal cutpoint in continuous gene expression measurement without prior biological knowledge or assumption and, as a result, enables systematic meta-analysis of multiple datasets. CONCLUSION: PrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets and would accelerate cancer research. The database is publicly accessible at http://gibk21.bse.kyutech.ac.jp/PrognoScan/index.html.
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Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
Gene-expression profiles predict survival of patients with lung adenocarcinoma
Beer, D. G., Kardia, S. L. R., Huang, C.-C., Giordano, T. J., Levin, A. M., Misek, D. E., Lin, L., Chen, G., Gharib, T. G., Thomas, D. G., et al. (2002) · Nature Medicine · doi:10.1038/nm733 · Cited by 2,025
Dangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors
Altman, D. G., Lausen, B., Sauerbrei, W., & Schumacher, M. (1994) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/86.11.829 · Cited by 1,143
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The prognostic landscape of genes and infiltrating immune cells across human cancers
Gentles, A. J., Newman, A. M., Liu, C. L., Bratman, S. V., Feng, W., Kim, D., Nair, V. S., Xu, Y., Khuong, A., Hoang, C. D., et al. (2015) · Nature Medicine · doi:10.1038/nm.3909 · Cited by 3,118
Okayama, H., Kohno, T., Ishii, Y., Shimada, Y., Shiraishi, K., Iwakawa, R., Furuta, K., Tsuta, K., Shibata, T., Yamamoto, S., et al. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-1403 · Cited by 874
Self-citationAguirre-Gamboa, R., Gomez-Rueda, H., Martínez-Ledesma, E., Martínez-Torteya, A., Chacolla-Huaringa, R., Rodriguez-Barrientos, A., Tamez-Peña, J. G., & Treviño, V. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074250 · Cited by 686
Comprehensive literature review and statistical considerations for microarray meta-analysis
Tseng, G. C., Ghosh, D., & Feingold, E. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1265 · Cited by 526
UCHL1 provides diagnostic and antimetastatic strategies due to its deubiquitinating effect on HIF-1α
Goto, Y., Zeng, L., Yeom, C. J., Zhu, Y., Morinibu, A., Shinomiya, K., Kobayashi, M., Hirota, K., Itasaka, S., Yoshimura, M., et al. (2015) · Nature Communications · doi:10.1038/ncomms7153 · Cited by 229
Metadata
- Authors
- Mizuno, H., Kitada, K., Nakai, K., & Sarai, A.
- Venue
- BMC Medical Genomics
- Published
- 2009-04-24
- Volume
- 2
- Issue
- 1
- Pages
- 18-18
- ISSN
- 1755-8794 (ISSN-L)
- OpenAlex
- W2048000549
- Cited by
- 995
- References
- 3
- FWCI
- 0.15
- Type
- journal article
- Language
- en
- Open access
- gold
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- Mizuno, H., Kitada, K., Nakai, K., & Sarai, A. (2009). PrognoScan: a new database for meta-analysis of the prognostic value of genes. BMC Medical Genomics. https://doi.org/10.1186/1755-8794-2-18
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
