The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Tissue microarray (TMA) technology: miniaturized pathology archives for high-throughputin situ studies
Open accessAbstract
Tissue microarray (TMA) technology allows a massive acceleration of studies correlating molecular in situ findings with clinico-pathological information. In this technique, cylindrical tissue samples are taken from up to 1000 different archival tissue blocks and subsequently placed into one empty 'recipient' paraffin block. Sections from TMA blocks can be used for all different types of in situ tissue analyses including immunohistochemistry and in situ hybridization. Multiple studies have demonstrated that findings obtained on TMAs are highly representative of their donor tissues, despite the small size of the individual specimens (diameter 0.6 mm). It is anticipated that TMAs will soon become a widely used tool for all types of tissue-based research. The availability of TMAs containing highly characterized tissues will enable every researcher to perform studies involving thousands of tumours rapidly. Therefore, TMAs will lead to a significant acceleration of the transition of basic research findings into clinical applications.
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
Tissue microarrays for high-throughput molecular profiling of tumor specimens
Kononen, J., Bubendorf, L., Kallionimeni, A., Bärlund, M., Schraml, P., Leighton, S., Torhorst, J., Mihatsch, M. J., Sauter, G., & Kallionimeni, O.-P. (1998) · Nature Medicine · doi:10.1038/nm0798-844 · Cited by 4,099
Self-citationUse of a cDNA microarray to analyse gene expression patterns in human cancer
(1996) · Nature Genetics · doi:10.1038/ng1296-457 · Cited by 1,951
Expression profiling using cDNA microarrays
Duggan, D. J., Bittner, M., Chen, Y., Meltzer, P., & Trent, J. M. (1999) · Nature Genetics · doi:10.1038/4434 · Cited by 1,657
Bubendorf, L., Kononen, J., Koivisto, P. A., Schraml, P., Moch, H., Gasser, T. C., Willi, N., Mihatsch, M. J., Sauter, G., & Kallioniemi, O. (1999) · PubMed · Cited by 594
Self-citationTissue microarrays for gene amplification surveys in many different tumor types.
Schraml, P., Kononen, J., Bubendorf, L., Moch, H., Bissig, H., Nocito, A., Mihatsch, M. J., Kallioniemi, O., & Sauter, G. (1999) · PubMed · Cited by 433
Self-citationMoch, H., Schraml, P., Bubendorf, L., Mirlacher, M., Kononen, J., Gasser, T., Mihatsch, M. J., Kallioniemi, O. P., & Sauter, G. (1999) · The American Journal of Pathology · doi:10.1016/s0002-9440(10)65349-7 · Cited by 391
Self-citationThe multitumor (sausage) tissue block: novel method for immunohistochemical antibody testing.
Battifora, H. A. (1986) · PubMed · Cited by 381
Bubendorf, L., Kolmer, M., Kononen, J., Koivisto, P., Mousses, S., Chen, Y., Mahlamaki, E., Schraml, P., Moch, H., Willi, N., et al. (1999) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/91.20.1758 · Cited by 350
Self-citationBarlund, M., Forozan, F., Kononen, J., Bubendorf, L., Chen, Y., Bittner, M. L., Torhorst, J., Haas, P., Bucher, C., Sauter, G., et al. (2000) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/92.15.1252 · Cited by 275
Self-citationRichter, J., Wagner, U., Kononen, J., Fijan, A., Bruderer, J., Schmid, U., Ackermann, D., Maurer, R., Alund, G., Knönagel, H., et al. (2000) · The American Journal of Pathology · doi:10.1016/s0002-9440(10)64592-0 · Cited by 242
Self-citationMultiple genes at 17q23 undergo amplification and overexpression in breast cancer.
Barlund, M. T., Monni, O. M., Kononen, J., Cornelison, R., Torhorst, J. K. H., Sauter, G., OLLI-P, K., & Kallioniemi, A. H. (2000) · PubMed · Cited by 199
Self-citation
Cited by
Frequent EpCam protein expression in human carcinomas
Went, P. T. H., Lugli, A., Meier, S., Bundi, M., Mirlacher, M., Sauter, G., & Dirnhofer, S. (2004) · Human Pathology · doi:10.1016/j.humpath.2003.08.026 · Cited by 819
Self-citationDifferential Gene Expression of Eph Receptors and Ephrins in Benign Human Tissues and Cancers
Hafner, C., Schmitz, G., Meyer, S., Bataille, F., Hau, P., Langmann, T., Dietmaier, W., Landthaler, M., & Vogt, T. (2004) · Clinical Chemistry · doi:10.1373/clinchem.2003.026849 · Cited by 323
Masiero, M., Simões, F. C., Han, H. D., Snell, C., Peterkin, T., Bridges, E., Mangala, L. S., Wu, S. Y.-Y., Pradeep, S., Li, D., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.06.004 · Cited by 313
Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer
Foersch, S., Glasner, C., Woerl, A.-C., Eckstein, M., Wagner, D.-C., Schulz, S., Kellers, F., Fernandez, A., Tserea, K., Kloth, M., et al. (2023) · Nature Medicine · doi:10.1038/s41591-022-02134-1 · Cited by 251
High Ep-CAM Expression is Associated with Poor Prognosis in Node-positive Breast Cancer
Spizzo, G., Gastl, G., Obrist, P., Went, P., Dirnhofer, S., Bischoff, S., Mirlacher, M., Sauter, G., Simon, R., Stopatschinskaya, S., et al. (2004) · Breast Cancer Research and Treatment · doi:10.1023/b:brea.0000036787.59816.01 · Cited by 254
Self-citation
Metadata
- Authors
- Bubendorf, L., Nocito, A., Moch, H., & Sauter, G.
- Venue
- The Journal of Pathology
- Publisher
- Wiley
- Published
- 2001
- Volume
- 195
- Issue
- 1
- Pages
- 72-79
- ISSN
- 0022-3417 (ISSN-L)
- 1096-9896
- OpenAlex
- W2049299149
- Cited by
- 398
- References
- 11
- FWCI
- 30.04
- Type
- journal article
- Language
- en
- Open access
- bronze
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
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.
