Pregnancy Associated Breast Cancer Gene Expressions : New Insights on Their Regulation Based on Rare Correlated Patterns
| dc.rights.license | open | en_US |
| dc.contributor.author | BOUASKER, Souad | |
| dc.contributor.author | INOUBLI, Wissem | |
| dc.contributor.author | YAHIA, Sadok Ben | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | DIALLO, Abdourahmane Gayo
IDREF: 112800084 | |
| dc.date.accessioned | 2021-07-15T10:30:18Z | |
| dc.date.available | 2021-07-15T10:30:18Z | |
| dc.date.issued | 2020-08-10 | |
| dc.identifier.issn | 1545-5963 | en_US |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/109250 | |
| dc.description.abstractEn | Breast-cancer (BC) is the most common invasive cancer in women, with considerable death. Given that, BC is classified as a hormone-dependent cancer, when it collides with pregnancy, different questions may arise for which there are still no convincing answers. To deal with this issue, two new frameworks are proposed within this paper: CoRaM and Dist-CoRaM. The former is the first unified framework dedicated to the extraction of a generic basis of Correlated-Rare Association rules from gene expression data. The proposed approach has been successfully applied on a breast-cancer Gene Expression Matrix (GSE1379) with very promising results. The latter, the Dist-CoRaM approach, is a big-data processing based on Apache spark framework, dealing with correlation mining from micro-array pregnancy associated breast-cancer assays (PABC) data. It is successfully applied on the (GSE31192) gene expression matrix (GEM). The correlated patterns of gene-sets shed light on the fact that PABC exhibits heightened aggressiveness compared to cancers for Non-PABC women. Our findings suggest that higher levels of estrogen and progesterone hormones, unfortunately, are very keen to the increase of the tumor aggressiveness and the proliferation of the cancer. | |
| dc.language.iso | EN | en_US |
| dc.subject.en | Correlation | |
| dc.subject.en | Pregnancy | |
| dc.subject.en | Gene expression | |
| dc.subject.en | Data mining | |
| dc.subject.en | Breast cancer | |
| dc.subject.en | Rarity | |
| dc.subject.en | Correlation | |
| dc.subject.en | Association rule | |
| dc.subject.en | Differentially-expressed genes | |
| dc.subject.en | Pregnancy associated breast cancer | |
| dc.subject.en | Distributed computing | |
| dc.subject.en | Apache spark | |
| dc.title.en | Pregnancy Associated Breast Cancer Gene Expressions : New Insights on Their Regulation Based on Rare Correlated Patterns | |
| dc.type | Article de revue | en_US |
| dc.identifier.doi | 10.1109/TCBB.2020.3015236 | en_US |
| dc.subject.hal | Sciences du Vivant [q-bio]/Santé publique et épidémiologie | en_US |
| dc.identifier.pubmed | 32776880 | en_US |
| bordeaux.journal | IEEE/ACM Transactions on Computational Biology and Bioinformatics | en_US |
| bordeaux.page | 1035-1048 | en_US |
| bordeaux.volume | 18 | en_US |
| bordeaux.hal.laboratories | Bordeaux Population Health Research Center (BPH) - UMR 1219 | en_US |
| bordeaux.issue | 3 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | INSERM | en_US |
| bordeaux.team | ERIAS | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| hal.export | false | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=IEEE/ACM%20Transactions%20on%20Computational%20Biology%20and%20Bioinformatics&rft.date=2020-08-10&rft.volume=18&rft.issue=3&rft.spage=1035-1048&rft.epage=1035-1048&rft.eissn=1545-5963&rft.issn=1545-5963&rft.au=BOUASKER,%20Souad&INOUBLI,%20Wissem&YAHIA,%20Sadok%20Ben&DIALLO,%20Abdourahmane%20Gayo&rft.genre=article |
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