English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The application of microarray and related technologies is currently generating a systematic catalog of the transcriptional response of any single gene to a multiplicity of experimental conditions. Clustering genes according to the similarity of their transcriptional response provides a direct hint to the regulons of the different transcription factors, many of which have still not been characterized. We have developed a new method for deciphering the mechanism underlying the common transcriptional response of a set of genes, i.e. discovering cis -acting regulatory elements from a set of unaligned upstream sequences. This method, called dyad analysis, is based on the observation that many regulatory sites consist of a pair of highly conserved trinucleotides, spaced by a non-conserved region of fixed width. The approach is to count the number of occurrences of each possible spaced pair of trinucleotides, and to assess its statistical significance. The method is highly efficient in the detection of sites bound by C(6)Zn(2)binuclear cluster proteins, as well as other transcription factors. In addition, we show that the dyad and single-word analyses are efficient for the detection of regulatory patterns in gene clusters from DNA chip experiments. In combination, these programs should provide a fast and efficient way to discover new regulatory sites for as yet unknown transcription factors.

Discovering regulatory elements in non-coding sequences by analysis of spaced dyads