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1 2, and 3.1% (31 of 1007) in CHEK2 or another breast cancer gene.
2 o 2000 was sequenced for known and candidate breast cancer genes.
3 ined, but <10% were shared with E2-regulated breast cancer genes.
4 identification of additional low-penetrance breast-cancer genes.
5 ely than other women to inherit mutations in breast-cancer genes.
8 us region of the 1863 residue early onset of breast cancer gene 1 (BRCA1) nuclear protein contains a
9 The carboxyl-terminal domain (BRCT) of the Breast Cancer Gene 1 (BRCA1) protein is an evolutionaril
10 tes binding sites for pairs of BRCT repeats (breast cancer gene 1 [BRCA1] C terminal repeats) in the
11 ing S phase, which recruits Brc1 through its breast cancer gene 1 protein (BRCA1) C-terminal (BRCT) d
13 rotein-protein interaction (PPI) mediated by breast-cancer-gene 1 C-terminal (BRCT) is an attractive
14 4%) carried a pathogenic mutation in another breast cancer gene (29 in CHEK2, and 1 each in BRIP1 and
15 he fact that 5 FA genes are in fact familial breast cancer genes and FA gene mutations are found freq
16 actors; however, the discovery of additional breast cancer genes and genes contributing to racial dis
17 veral panel genes as high- and moderate-risk breast cancer genes and provides estimates of breast can
18 gamma transcription factor regulates luminal breast cancer genes, and loss of TFAP2C induces epitheli
30 ter exclusion of BRCA1, BRCA2, and syndromic breast cancer genes (CDH1, PTEN, and TP53), observed pat
32 investigate long-range interactions at three breast cancer gene deserts mapping to 2q35, 8q24.21, and
36 d utility of this method, we applied it to a breast cancer gene expression dataset and tested its abi
37 ation experiments using multiple independent breast cancer gene expression datasets and PPI networks.
38 rom public data repositories a collection of breast cancer gene expression datasets with over 7000 pa
39 Through integrative analysis of clinical breast cancer gene expression datasets, cell line models
40 essenger RNA (mRNA) profiling of transfected breast cancer gene expression in a living cell is demons
41 ented and performed a large meta-analysis of breast cancer gene expression profiles from 223 datasets
45 and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2
47 te that the products of BRCA1, neu, and erbB breast cancer genes participate in a common or shared si
49 nds identified as inversely connected to the breast cancer gene signatures, 14 of them are known anti
51 d expression of a previously uncharacterized breast cancer gene that encodes a secreted protein desig
52 ceptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estr
53 e that EpCAM is a potential novel target for breast cancer gene therapy and offer insights into the m
54 ess the value of EpCAM as a novel target for breast cancer gene therapy, we performed real-time rever
56 nds was sequenced for 23 known and candidate breast cancer genes using BROCA, a targeted multiplexed
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