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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A major thrust in the field of computational intelligence is the ability to comprehend and interpret intelligence in combination with several research disciplines of computer science, biology, statistics, and cognitive science. The emergence of bio informatics is a two-fold manifestation of advance biology along with data mining and statistical learning that attempts to analyse and interpret a large collection of medical data. It aims at exploring facts about unknown patterns. This paper aims at providing a model that numerically analyses the existence of carcinomas in the genomic data sequence. Attempts have been taken to optimise the highly contributing factors using recent nature inspired algorithms like Emperor Penguin Optimization Algorithm (EPOA) and Chaotic Artificial Algae Optimization(CAAO). These algorithms are gaining popularity as they are capable of exploring global optimum instead of local optimum. The performance of these algorithms are judged by implementing it in seven benchmark datasets. To ensure a good potential of these new algorithms, we have made a comparative study with the capability of other indigenous optimization algorithms like PSO etc.

Integrating Numerical and Quantitative Techniques for Analysis of Large-Scale Biological data using Hyper-heuristic Algorithm