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TF2LncRNA:从 ChIP-Seq 数据中为一组 lncRNA 基因识别常见转录因子。

TF2LncRNA: identifying common transcription factors for a list of lncRNA genes from ChIP-Seq data.

机构信息

School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.

School of Software, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.

出版信息

Biomed Res Int. 2014;2014:317642. doi: 10.1155/2014/317642. Epub 2014 Mar 4.

Abstract

High-throughput genomic technologies like lncRNA microarray and RNA-Seq often generate a set of lncRNAs of interest, yet little is known about the transcriptional regulation of the set of lncRNA genes. Here, based on ChIP-Seq peak lists of transcription factors (TFs) from ENCODE and annotated human lncRNAs from GENCODE, we developed a web-based interface titled "TF2lncRNA," where TF peaks from each ChIP-Seq experiment are crossed with the genomic coordinates of a set of input lncRNAs, to identify which TFs present a statistically significant number of binding sites (peaks) within the regulatory region of the input lncRNA genes. The input can be a set of coexpressed lncRNA genes or any other cluster of lncRNA genes. Users can thus infer which TFs are likely to be common transcription regulators of the set of lncRNAs. In addition, users can retrieve all lncRNAs potentially regulated by a specific TF in a specific cell line of interest or retrieve all TFs that have one or more binding sites in the regulatory region of a given lncRNA in the specific cell line. TF2LncRNA is an efficient and easy-to-use web-based tool.

摘要

高通量基因组技术,如 lncRNA 微阵列和 RNA-Seq,通常会产生一组感兴趣的 lncRNAs,但对于这组 lncRNA 基因的转录调控知之甚少。在这里,我们基于 ENCODE 的转录因子 (TF) 的 ChIP-Seq 峰列表和 GENCODE 注释的人类 lncRNAs,开发了一个名为“TF2lncRNA”的基于网络的界面,其中每个 ChIP-Seq 实验的 TF 峰都与一组输入 lncRNAs 的基因组坐标交叉,以确定哪些 TF 在输入 lncRNA 基因的调节区域内呈现出数量上显著的结合位点(峰)。输入可以是一组共表达的 lncRNA 基因,也可以是任何其他 lncRNA 基因簇。用户因此可以推断哪些 TF 可能是一组 lncRNAs 的常见转录调节剂。此外,用户可以检索特定细胞系中特定 TF 可能调节的所有 lncRNAs,或者检索特定细胞系中给定 lncRNA 调节区域中具有一个或多个结合位点的所有 TF。TF2LncRNA 是一种高效易用的基于网络的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e94/3960524/17e65a8c529e/BMRI2014-317642.001.jpg

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