Search

Abstract This research work focus on the multiple sequence alignment, as developing an exact multiple sequence alignment for different protein sequences is a difficult computational task. In this research, a hybrid algorithm named Bacterial Foraging Optimization-Genetic Algorithm (BFO-GA) algorithm is aimed to improve the multi-objectives and carrying out measures of multiple sequence alignment. The proposed algorithm employs multi-objectives such as variable gap penalty minimization, maximization of similarity and non-gap percentage. The proposed BFO-GA algorithm is measured with various MSA methods such as T-Coffee, Clustal Omega, Muscle, K-Align, MAFFT, GA, ACO, ABC and PSO. The experiments were taken on four benchmark datasets such as BAliBASE 3.0, Prefab 4.0, SABmark 1.65 and Oxbench 1.3 databases and the outcomes prove that the proposed BFO-GA algorithm obtains better statistical significance results as compared with the other well-known methods. This research study also evaluates the practicability of the alignments of BFO-GA by applying the optimal sequence to predict the phylogenetic tree by using ClustalW2 Phylogeny tool and compare with the existing algorithms by using the Robinson-Foulds (RF) distance performance metric. Lastly, the statistical implication of the proposed algorithm is computed by using the Wilcoxon Matched-Pair Signed- Rank test and also it infers better results.

Pesticide resistance is a common concern. It exerts close association with economic and health associated problems in various plants and other organisms. Several approaches have been trialled for attracting and trapping the insects and flies that are acting as vectors for transmission of communicable diseases. Although Drosophila melanogaster (fruit flies) is not an agricultural pest, its presence in consumer dwelling areas is an objection to human, as it indicates signs of an unhealthy environment or products. The current study focuses on the development of nanoemulsion with synthetic attractants and entrapping in sticky glue formulation that could provide prolonged effect for attracting and trapping the fruit flies. The results of our study showed the efficient attractive ability of exposed nanoemulsion (A3E1T) containing amyl acetate, ammonia, ethanol and Tween 80 compared to that of control. While the sex-based effect was not very prominent, the nanoemulsion showed a higher relative response index to the flies and increased activity even during their siesta time. Therefore, the nanoemulsion-based approach could be identified as one of the promising lines of attack and a suitable alternative for the existing fruit fly control measures. The present study is the first of its kind in reporting the ability of nanoemulsion formulation to attract and influence the activity of fruit flies D. melanogaster, up to our best of knowledge.