Destiny from density
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Significantly SV genes in breast cancer were enriched for collagens, which distinguish tissue substructure (Reactome "Collagen formation", P = 3.38 * 10-14).
“Significantly SV genes were enriched for collagens, which distinguish tissue substructure13 (Reactome “Collagen formation”, P = 3.38 * 10-14, gProfiler14, Supp. Table 1).”
From SpatialDE: identification of spatially variable genes (2018) · cites this paper as [13]
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DeFilippis, R. A., Chang, H., Dumont, N., Rabban, J. T., Chen, Y.-Y., Fontenay, G. V., Berman, H. K., Gauthier, M. L., Zhao, J., Hu, D., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0107 · Cited by 212 · see citing works
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Research works printed but not linked: 13
- [1]King M-C Science 2003 302 643 646 14576434
- [2]John EM JAMA 2007 298 2869 2876 18159056
- [3]Shih HA J. Clin. Oncol 2002 27 994 999 11844822
- [4]Arendt LM Rudnick JA Keller PJ Kuperwasser C Semin. Cell Dev. Biol 2010 21 11 18 19857593 PMC2823823
- [5]Conklin MW Am. J Pathol 2011 178 1221 1232 21356373 PMC3070581
- [6]Boyd NF N. Engl. J. Med 2002 347 886 894 12239257
- [7]DeFilippis RA Cancer Discov 2012 2 826 839 22777768 PMC3457705
- [8]Maller O Martinson H Schedin PJ Mammary Gland Biol. Neoplasia 2010 15 301 318 20811805
- [9]Place AE Huh SJ Polyak K Breast Cancer Res 2011 13 227 22078026 PMC3326543
- [10]Nakasone ES Cancer Cell 2012 21 488 503 22516258 PMC3332002
- [11]Walker RA Breast Cancer Res 2001 3 143 145 11305947 PMC138677
- [12]Lehman CD Cancer 2005 103 1898 1905 15800894
- [13]Silverstein RL Febbraio M Sci. Signal 2009 2 re3 PMC2811062 19471024
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SpatialDE: identification of spatially variable genes
Svensson, V., Teichmann, S. A., & Stegle, O. (2018) · Nature Methods · doi:10.1038/nmeth.4636 · Cited by 695 · see citing works
- Authors
- Seewaldt, V. L.
- Affiliations
- Duke University (US)
- Corresponding author
- Seewaldt, Victoria L.
- Venue
- Nature
- Published
- 2012-10-24
- Volume
- 490
- Issue
- 7421
- Pages
- 490-491
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3640457
- OpenAlex
- W1990337132
- Cited by
- 7
- References
- 1
- Citations by year
- 2025: 1 · 2018: 2 · 2015: 1 · 2014: 2 · 2013: 1
- FWCI
- 1.00
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Cancer Institute (R01CA158668, R01CA114068, R01CA155664)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Digital Radiography and Breast Imaging
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- breast density, breast cancer risk, connective tissue, signalling proteins, risk prediction markers, breast tissue
- MeSH terms
- Aging, Breast Neoplasms, Collagen, Female, Humans, Obesity, Biomarkers, Tumor, Signal Transduction, Stromal Cells, Risk Assessment, CD36 Antigens, White People, Cellular Microenvironment, Hereditary Breast and Ovarian Cancer Syndrome
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.
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