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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Background: Current research suggests that a small set of "driver" mutationsare responsible for tumorigenesis while a larger body of "passenger" mutationsoccurs in the tumor but does not progress the disease. Due to recentpharmacological successes in treating cancers caused by driver mutations, avariety of of methodologies that attempt to identify such mutations have beendeveloped. Based on the hypothesis that driver mutations tend to cluster in keyregions of the protein, the development of cluster identification algorithmshas become critical.  Results: We have developed a novel methodology, SpacePAC (Spatial ProteinAmino acid Clustering), that identifies mutational clustering by consideringthe protein tertiary structure directly in 3D space. By combining themutational data in the Catalogue of Somatic Mutations in Cancer (COSMIC) andthe spatial information in the Protein Data Bank (PDB), SpacePAC is able toidentify novel mutation clusters in many proteins such as FGFR3 and CHRM2. Inaddition, SpacePAC is better able to localize the most significant mutationalhotspots as demonstrated in the cases of BRAF and ALK. The R package isavailable on Bioconductor at:http://www.bioconductor.org/packages/release/bioc/html/SpacePAC.html  Conclusion: SpacePAC adds a valuable tool to the identification of mutationalclusters while considering protein tertiary structure

A Spatial Simulation Approach to Account for Protein Structure When Identifying Non-Random Somatic Mutations