SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles | Zendy

KaChun Wong | Zendy; Yue Li | Zendy; Chengbin Peng | Zendy; Zhaolei Zhang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles

Author(s) -

KaChun Wong,

Yue Li,

Chengbin Peng,

Zhaolei Zhang

Publication year - 2014

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/btu604

Subject(s) - chromatin immunoprecipitation , computational biology , cluster analysis , decipher , computer science , encode , biology , tiling array , probabilistic logic , transcription factor , genome , enhancer , chip sequencing , dna microarray , gene , genetics , promoter , artificial intelligence , chromatin remodeling , gene expression

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene being expressed in different tissues or at different developmental stages. To fully understand the functions of genes, it is essential to develop probabilistic models on multiple ChIP-Seq profiles to decipher the combinatorial regulatory mechanisms by multiple transcription factors.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research