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TF2Network : predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information

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Bioinformatics: from nucleotids to networks (N2N)
Abstract
A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidop-sis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75-92% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response.
Keywords
COEXPRESSION NETWORKS, COMPARATIVE GENOMICS, PROMOTER SEQUENCES, DNA, ELEMENTS, PLANT GENE, THALIANA, EXPRESSION, DATABASE, TOOLS, IDENTIFICATION

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  • Kulkarni et al. (2018) Nucleic Acids Research 46,e31.pdf
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Chicago
Kulkarni, Shubhada Rajabhau, Dries Vaneechoutte, Jan Van de Velde, and Klaas Vandepoele. 2018. “TF2Network : Predicting Transcription Factor Regulators and Gene Regulatory Networks in Arabidopsis Using Publicly Available Binding Site Information.” Nucleic Acids Research 46 (6).
APA
Kulkarni, S. R., Vaneechoutte, D., Van de Velde, J., & Vandepoele, K. (2018). TF2Network : predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information. NUCLEIC ACIDS RESEARCH, 46(6).
Vancouver
1.
Kulkarni SR, Vaneechoutte D, Van de Velde J, Vandepoele K. TF2Network : predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information. NUCLEIC ACIDS RESEARCH. 2018;46(6).
MLA
Kulkarni, Shubhada Rajabhau, Dries Vaneechoutte, Jan Van de Velde, et al. “TF2Network : Predicting Transcription Factor Regulators and Gene Regulatory Networks in Arabidopsis Using Publicly Available Binding Site Information.” NUCLEIC ACIDS RESEARCH 46.6 (2018): n. pag. Print.
@article{8563189,
  abstract     = {A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidop-sis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75-92\% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response.},
  articleno    = {e31},
  author       = {Kulkarni, Shubhada Rajabhau and Vaneechoutte, Dries and Van de Velde, Jan and Vandepoele, Klaas},
  issn         = {0305-1048},
  journal      = {NUCLEIC ACIDS RESEARCH},
  keyword      = {COEXPRESSION NETWORKS,COMPARATIVE GENOMICS,PROMOTER SEQUENCES,DNA,ELEMENTS,PLANT GENE,THALIANA,EXPRESSION,DATABASE,TOOLS,IDENTIFICATION},
  language     = {eng},
  number       = {6},
  pages        = {15},
  title        = {TF2Network : predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information},
  url          = {http://dx.doi.org/10.1093/nar/gkx1279},
  volume       = {46},
  year         = {2018},
}

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