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/

Zendy Plus

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

Zendy Tools

Zendy Open

Uncovering functional associations for genes and gene products remains one of the most significant challenges in biology. The classical approaches, such as homology detection, are mainly suited for predicting approximate molecular function of a protein and should be used in context with other methods. Several studies have emerged that employ knowledge-based procedures to extract functional data for genes from a variety of biological sources. However, data derived from a single biological resource often provides only a limited perspective on their functional associations largely due to systematic bias in the underlying data. The post-genomic era has witnessed the emergence of knowledge-based studies that aim to decipher functional associations by combining several biological evidence types. These are expected to provide better insights into the functional aspects of diverse genes, genomes and networks.

Integrating information from existing databases for enhanced function annotation of genes, genomes and networks