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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

BLAST is a standard tool in bioinformatics for creating local sequencealignments using a "seed-and-extend" approach. Here we introduce an analogousseed-and-extend algorithm that produces local network alignments: BLANT (BasicLocal Alignment of Network Topology). In Part 1, we introduced BLANT-seed,which generates graphlet-based seeds using only topological information. Here,in Part 2, we describe BLANT-extend, which "grows" seeds to larger localalignments using only topological information. We allow the user to specifybounds on several measures an alignment must satisfy, including the edgedensity, edge commonality (i.e., aligned edges), and node-pair similarity ifsuch a measure is used; the latter allows the inclusion of sequence-basedsimilarity, if desired, as well as local topological constraints. BLANT-extendis able to enumerate all possible alignments satisfying the bounds that can begrown from each seed, within a specified CPU time or number of generatedalignments. While topology-driven local network alignment has a wide variety ofpotential applications outside bioinformatics, here we focus on the alignmentof Protein-Protein Interaction (PPI) networks. We show that BLANT is capable offinding large, high-quality local alignments when the networks are known tohave high topological similarity -- for example recovering hundreds oforthologs between networks of the recent Integrated Interaction Database (IID).Predictably, however, it performs less well when true topological similarity isabsent, as is the case in most current experimental PPI networks that are noisyand have wide disparity in edge density which results in low common coverage.

BLANT: Basic Local Alignment of Network Topology, Part 2: Topology-only Extension Beyond Graphlet Seeds