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PubMed:16608396 JSONTXT 8 Projects

Annnotations TAB TSV DIC JSON TextAE Lectin_function IAV-Glycan

Id Subject Object Predicate Lexical cue
TextSentencer_T1 0-97 Sentence denotes Multilocus genotypes spanning estrogen metabolism associated with breast cancer and fibroadenoma.
T1 0-97 Sentence denotes Multilocus genotypes spanning estrogen metabolism associated with breast cancer and fibroadenoma.
TextSentencer_T2 98-361 Sentence denotes We investigated inherited polymorphic variation in genes spanning estrogen metabolism (10 SNPs [single nucleotide polymorphism]) to distinguish multilocus genotypes associated with breast cancer (n = 393), benign breast lesions (n = 154), and low risk (n = 1936).
T2 98-361 Sentence denotes We investigated inherited polymorphic variation in genes spanning estrogen metabolism (10 SNPs [single nucleotide polymorphism]) to distinguish multilocus genotypes associated with breast cancer (n = 393), benign breast lesions (n = 154), and low risk (n = 1936).
TextSentencer_T3 362-685 Sentence denotes Three latent classification GoM extreme type groups represented the data: (a) fibroadenoma, and infrequent SRD5A2 and VDR alleles; (b) postmenopausal breast cancer, and infrequent CYP1A1-1 and CYP1A1-2 alleles (both over-represented infrequent alleles for CYP17, CYP19-3, and COMT); and (c) women at intrinsically low risk.
T3 362-685 Sentence denotes Three latent classification GoM extreme type groups represented the data: (a) fibroadenoma, and infrequent SRD5A2 and VDR alleles; (b) postmenopausal breast cancer, and infrequent CYP1A1-1 and CYP1A1-2 alleles (both over-represented infrequent alleles for CYP17, CYP19-3, and COMT); and (c) women at intrinsically low risk.
TextSentencer_T4 686-757 Sentence denotes Carriage of the respective multilocus genotypes increased risk 25-fold.
T4 686-757 Sentence denotes Carriage of the respective multilocus genotypes increased risk 25-fold.
TextSentencer_T5 758-879 Sentence denotes We conclude that GoM latent classification may be useful to identify genetic risk sets and estimate risk for individuals.
T5 758-879 Sentence denotes We conclude that GoM latent classification may be useful to identify genetic risk sets and estimate risk for individuals.