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NURBS: a database of experimental and predicted nuclear receptor binding sites of mouse
Author(s) -
Yaping Fang,
HuiXin Liu,
Ning Zhang,
Grace L. Guo,
YuJui Yvonne Wan,
Jianwen Fang
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts693
Subject(s) - hidden markov model , computer science , chromatin immunoprecipitation , genome browser , visualization , computational biology , binding site , dna binding site , database , data mining , genome , biology , artificial intelligence , genetics , gene , genomics , promoter , gene expression
Nuclear receptors (NRs) are a class of transcription factors playing important roles in various biological processes. An NR often impacts numerous genes and different NRs share overlapped target networks. To fulfil the need for a database incorporating binding sites of different NRs at various conditions for easy comparison and visualization to improve our understanding of NR binding mechanisms, we have developed NURBS, a database for experimental and predicted nuclear receptor binding sites of mouse (NURBS). NURBS currently contains binding sites across the whole-mouse genome of 8 NRs identified in 40 chromatin immunoprecipitation with massively parallel DNA sequencing experiments. All datasets are processed using a widely used procedure and same statistical criteria to ensure the binding sites derived from different datasets are comparable. NURBS also provides predicted binding sites using NR-HMM, a Hidden Markov Model (HMM) model.

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