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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Using cis-regulatory motifs known to regulate plant osmotic stress response, an artificial neural network model was built to identify other functionally releted genes involved in the same process. The rationale behind our approach is that gene expression is largely controlled at the transcriptional level through the interactions between transcription factors and cis-regulatory elements. Gene Ontology enrichment analysis on the 500 top-scoring predictions showed that, 60% of the enriched GO classification was related to stress response. RT-PCR analysis showed that nearly 70% of the top-scoring predictions exhibited altered expression under various stress treatments. We expect that similar approach is widely applicable to infer gene function in various cellular processes in different species.

Cis-regulatory element based gene finding: an application in Arabidopsis thaliana.