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

Comparative analyses of protein-protein interaction networks play importantroles in the understanding of biological processes. However, the growingenormity of available data on the networks becomes a computational challengefor the conventional alignment algorithms. Quantum algorithms generally providegreater efficiency over their classical counterparts in solving variousproblems.  One of such algorithms is the quantum phase estimation algorithm whichgenerates the principal eigenvector of a stochastic matrix with probabilityone.  Using the quantum phase estimation algorithm, we introduce a quantumcomputing approach for the alignment of protein-protein interaction networks byfollowing the classical algorithm IsoRank which uses the principal eigenvectorof the stochastic matrix representing the Kronecker product of the normalizedadjacency matrices of networks for the pairwise alignment. We also present agreedy quantum measurement scheme to efficiently procure the alignment from theoutput state of the phase estimation algorithm where the eigenvector is encodedas the amplitudes of this state. The complexity of the quantum approachoutperforms the classical running time.

Quantum IsoRank: Efficient Alignment of Multiple PPI Networks