data-raw/ITFP/README.md

In slowkow/tftargets: Human Transcription Factor Targets

ITFP: an integrated platform of mammalian transcription factors

Guangyong Zheng, Kang Tu, Qing Yang, Yun Xiong, Chaochun Wei, Lu Xie, Yangyong Zhu, and Yixue

http://dx.doi.org/10.1093/bioinformatics/btn439

Summary

Investigation of transcription factors (TFs) and their downstream regulated genes (targets) is a significant issue in post-genome era, which can provide a brand new vision for some vital biological process. However, information of TFs and their targets in mammalian is far from sufficient. Here, we developed an integrated TF platform (ITFP), which included abundant TFs and their targets of mammalian. In current release, ITFP includes 4105 putative TFs and 69 496 potential TF-target pairs for human, 3134 putative TFs and 37 040 potential TF-target pairs for mouse, and 1114 putative TFs and 18 055 potential TF-target pairs for rat. In short, ITFP will serve as an important resource for the research community of transcription and provide strong support for regulatory network study.

ITFP Website

http://itfp.biosino.org/itfp

Introduction

Investigation of transcription factors (TFs) and their downstream regulated genes (targets) is an important issue in post genome era, which can provide brand new vision for some vital biological process. However information of TFs and their targets in mammalian is far from sufficient. Here,we developed an integrated transcription factor platform (ITFP), which included abundant TFs and targets message of mammalian.

In our work, support vector machine (SVM) algorithm combined with error-correcting output coding (ECOC) algorithm was utilized to identify and classify transcription factor from protein sequence of Human, Mouse and Rat. For transcription factor targets, a reverse engineering method named ARACNE was used to derive potential interaction pairs between transcription factor and downstream regulated gene from Human, Mouse and Rat gene expression profile data. Detailed information of gene expression profile data can be found in help page. Moreover, all data provided by the platform is free for non-commercial users and can be downloaded through links on help page.

You can get release history of ITFP here. For current release, statistic information about TFs and interaction pairs between TF and target was depicted in following table:

Species             Transcription Factors   TF and Target Pairs     TFs with Target Information
Homo Sapiens        4105                    69496                   1974
Mus musculus        3134                    37040                   1340
Rattus norvegicus   1114                    18055                   541

Reference

1. The combination approach of SVM and ECOC for powerful identification and classification of transcription factor, Guangyong Zheng, Ziliang Qian, Qing Yang, Chaochun Wei, Lu Xie, Yangyong Zhu and Yixue Li, BMC Bioinformatics 2008, 9:282.

2. ITFP: an integrated platform of mammalian transcription factors, Guangyong Zheng, Kang Tu, Qing Yang, Yun Xiong, Chaochun Wei, Lu Xie, Yangyong Zhu, and Yixue Li, Bioinformatics 2008 24(20):2416-2417.

3. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context, Margolin, A.A., Nemenman, I., Basso, K., Wiggins, C., Stolovitzky, G., Dalla Favera, R. and Califano, A. BMC Bioinformatics 2006, 7 Suppl 1, S7.

slowkow/tftargets documentation built on May 30, 2019, 3:06 a.m.