The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Analyses of p53 Target Genes in the Human Genome by Bioinformatic and Microarray Approaches
Open accessAbstract
The completion of the human genome sequence (International Human Genome Sequence Consortium (2001) Nature 409, 860-921; Venter, J. C., et al. (2001) Science 291, 1304-1351) allows for new ways to analyze global cellular regulatory mechanisms. Here we present a strategy to identify genes regulated by specific transcription factors in the human genome, and apply it to p53. We first collected promoters or introns of all genes available using two methods: GenBank(TM) annotation and a computationally derived transcript map. 4,852 genes analyzed in this way contained at least one p53 consensus binding sequence. Of 13 genes randomly selected for mRNA analysis, 11 were shown to respond to p53 expression. Five promoters were analyzed by chromatin immunoprecipitation, which revealed that all were bound by p53 in vivo. We then analyzed 33,615 unique human genes on cDNA microarrays, identifying 1,501 genes that respond to p53 expression. A parameter was derived that demonstrates that in silico prediction greatly enriches for genes that are activated and repressed by p53 and assists us to suggest other signaling pathways that may be connected to p53. The methods shown here illustrate a novel approach to analysis of global gene regulatory network through the integration of human genomic sequence information and genome-wide gene expression analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Vogelstein, B., Lane, D., & Levine, A. J. (2000) · Nature · doi:10.1038/35042675 · Cited by 6,607
Tumor suppressor p53 is a direct transcriptional activator of the human bax gene
Toshiyuki, M., & Reed, J. C. (1995) · Cell · doi:10.1016/0092-8674(95)90412-3 · Cited by 4,063
Definition of a consensus binding site for p53
El-Deiry, W. S., Kern, S. E., Pietenpol, J. A., Kinzler, K. W., & Vogelstein, B. (1992) · Nature Genetics · doi:10.1038/ng0492-45 · Cited by 1,985
p53 Suppresses the Activation of the Bcl-2 Promoter by the Brn-3a POU Family Transcription Factor
Budhram-Mahadeo, V., Morris, P. J., Smith, M. D., Midgley, C. A., Boxer, L. M., & Latchman, D. S. (1999) · Journal of Biological Chemistry · doi:10.1074/jbc.274.21.15237 · Cited by 144
Shin, T. H., Paterson, A. J., & Kudlow, J. E. (1995) · Molecular and Cellular Biology · doi:10.1128/mcb.15.9.4694 · Cited by 78
Cited by
Transcriptional control of human p53-regulated genes
Riley, T., Sontag, E., Chen, P., & Levine, A. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2395 · Cited by 1,921
The transcription factor p53: Not a repressor, solely an activator.
Fischer, M., Steiner, L., & Engeland, K. (2014) · Cell Cycle · doi:10.4161/15384101.2014.949083 · Cited by 153
Jackson, J. G., & Pereira-Smith, O. M. (2006) · Molecular and Cellular Biology · doi:10.1128/mcb.26.7.2501-2510.2006 · Cited by 108
High-Affinity Binding of Tumor-Suppressor Protein p53 and HMGB1 to Hemicatenated DNA Loops
Štros, M., Muselíková-Polanská, E., Pospíšilová, Š., & Strauss, F. (2004) · Biochemistry · doi:10.1021/bi049928k · Cited by 81
Transcriptional networks and cellular senescence in human mammary fibroblasts.
Hardy, K., Mansfield, L., Mackay, A., Benvenuti, S., Ismail, S., Arora, P., O'Hare, M. J., & Jat, P. S. (2005) · Molecular Biology of the Cell · doi:10.1091/mbc.e04-05-0392 · Cited by 71
Metadata
- Authors
- Wang, L., Wu, Q., Qiu, P., Mirza, A., McGuirk, M., Kirschmeier, P., Greene, J. R., Wang, Y., Pickett, C. B., & Liu, S.
- Venue
- Journal of Biological Chemistry
- Publisher
- Elsevier BV
- Published
- 2001-11
- Volume
- 276
- Issue
- 47
- Pages
- 43604-43610
- ISSN
- 0021-9258 (ISSN-L)
- OpenAlex
- W1976842438
- Cited by
- 166
- References
- 5
- FWCI
- 6.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Analyses of p53 Target Genes in the Human Genome by Bioinformatic and Microarray Approaches. https://app.cochat.ai/papers/10.1074/jbc.m106570200
- The paper
- Wang, L., Wu, Q., Qiu, P., Mirza, A., McGuirk, M., Kirschmeier, P., Greene, J. R., Wang, Y., Pickett, C. B., & Liu, S. (2001). Analyses of p53 Target Genes in the Human Genome by Bioinformatic and Microarray Approaches. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.m106570200
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.