Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 408511
Title Visualizing and characterizing In Vivo DNA-Binding Events and Direct Target Genes of Plant Transcription Factors.
Author(s) Muino, J.M.; Angenent, G.C.; Kaufmann, K.
Source In: Plant Transcription Factors, Methods in Molecular Biology / Yuan, L., Perry, S.E., Springer Science (754 17) - p. 293 - 305.
Department(s) PRI BIOS Plant Development Systems
Laboratory of Molecular Biology
PRI Bioscience
Publication type Peer reviewed book chapter
Publication year 2011
Abstract Physical interactions between transcription factors and specific DNA sites are essential for gene regulation. Recent progress in genome-wide in vivo techniques, like chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-SEQ), enables plant researchers to generate genome-wide, high-resolution DNA-binding maps of transcription factors. These new types of data require the use of advanced bioinformatic tools in order to understand the molecular mechanisms of functional specificity and target gene regulation by transcription factors. Here, we will review the use of a genome browser to visualize genome-wide DNA-binding maps of plant transcription factors along with other publicly available data and the program MEME to determine DNA sequence motifs in the bound regions. We also describe a tool for functional classification of target genes using GO annotations. Analysis of transcriptional regulatory networks requires the integration of multiple types of data, and this chapter aims at giving an overview about different bioinformatic approaches for meta-analysis and data integration.
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