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

Gene expression measurements are a powerful tool in molecular biology, but when applied to heterogeneous samples containing more than one cellular type the results are difficult to interpret. We present here a new approach to this problem allowing to deduce the gene expression profile of the various cellular types contained in a set of samples directly from the measurements taken on the whole sample.

Separation of samples into their constituents using gene expression data