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

Genes carry the instructions for making proteins that are found in a cell asa specific sequence of nucleotides that are found in DNA molecules. But, theregions of these genes that code for proteins may occupy only a small region ofthe sequence. Identifying the coding regions play a vital role in understandingthese genes. In this paper we propose a unsupervised Fuzzy Multiple AttractorCellular Automata (FMCA) based pattern classifier to identify the coding regionof a DNA sequence. We propose a distinct K-Means algorithm for designing FMACAclassifier which is simple, efficient and produces more accurate classifierthan that has previously been obtained for a range of different sequencelengths. Experimental results confirm the scalability of the proposedUnsupervised FCA based classifier to handle large volume of datasetsirrespective of the number of classes, tuples and attributes. Goodclassification accuracy has been established.

Identification of Protein Coding Regions in Genomic DNA Using Unsupervised FMACA Based Pattern Classifier