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

Bi-clustering refers to the task of finding sub-matrices (indexed by a groupof columns and a group of rows) within a matrix of data such that the elementsof each sub-matrix (data and features) are related in a particular way, forinstance, that they are similar with respect to some metric. In this paper,after analyzing the well-known Cheng and Church (CC) bi-clustering algorithmwhich has been proved to be an effective tool for mining co-expressed genes.However, Cheng and Church bi-clustering algorithm and summarizing itslimitations (such as interference of random numbers in the greedy strategy;ignoring overlapping bi-clusters), we propose a novel enhancement of theadaptive bi-clustering algorithm, where a shielding complex sub-matrix isconstructed to shield the bi-clusters that have been obtained and to discoverthe overlapping bi-clusters. In the shielding complex sub-matrix, the imaginaryand the real parts are used to shield and extend the new bi-clusters,respectively, and to form a series of optimal bi-clusters. To assure that theobtained bi-clusters have no effect on the bi-clusters already produced, a unitimpulse signal is introduced to adaptively detect and shield the constructedbi-clusters. Meanwhile, to effectively shield the null data (zero-size data),another unit impulse signal is set for adaptive detecting and shielding. Inaddition, we add a shielding factor to adjust the mean squared residue score ofthe rows (or columns), which contains the shielded data of the sub-matrix, todecide whether to retain them or not. We offer a thorough analysis of thedeveloped scheme. The experimental results are in agreement with thetheoretical analysis. The results obtained on a publicly available realmicroarray dataset show the enhancement of the bi-clusters performance thanksto the proposed method.

An Enhanced Adaptive Bi-clustering Algorithm through Building a Shielding Complex Sub-Matrix