A hidden Markov model to identify combinatorial epigenetic regulation patterns for estrogen receptor α target genes.
about
Comparative annotation of functional regions in the human genome using epigenomic dataLOcating non-unique matched tags (LONUT) to improve the detection of the enriched regions for ChIP-seq dataNuclear-encoded mitochondrial MTO1 and MRPL41 are regulated in an opposite epigenetic mode based on estrogen receptor status in breast cancer.Transcription factor-associated combinatorial epigenetic pattern reveals higher transcriptional activity of TCF7L2-regulated intragenic enhancers.Incorporating domain knowledge in chemical and biomedical named entity recognition with word representations
P2860
A hidden Markov model to identify combinatorial epigenetic regulation patterns for estrogen receptor α target genes.
description
2012 nî lūn-bûn
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2012年の論文
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name
A hidden Markov model to ident ...... rogen receptor α target genes.
@en
type
label
A hidden Markov model to ident ...... rogen receptor α target genes.
@en
prefLabel
A hidden Markov model to ident ...... rogen receptor α target genes.
@en
P2860
P356
P1433
P1476
A hidden Markov model to ident ...... rogen receptor α target genes.
@en
P2093
Russell Bonneville
Victor X Jin
P2860
P356
10.1093/BIOINFORMATICS/BTS639
P407
P577
2012-10-26T00:00:00Z