The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, which is used to cluster genes. FCM allows an object to belong to two or more clusters with a membership grade between zero and one and the sum of belonging to all clusters of each gene is equal to one. This paradigm is useful when dealing with microarray data. The total time required to implement the first model is 22.2589 s. The second model combines FCM and particle swarm optimization (PSO) to obtain better results. The hybrid algorithm, i.e., FCM–PSO, uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–PSO method is effective. The total time of implementation of this model is 89.6087 s. The third model combines FCM with a genetic algorithm (GA) to obtain better results. This hybrid algorithm also uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–GA method is effective. Its total time of implementation is 50.8021 s. In addition, this study uses cluster validity indexes to determine the best partitioning for the underlying data. Internal validity indexes include the Jaccard, Davies Bouldin, Dunn, Xie–Beni, and silhouette. Meanwhile, external validity indexes include Minkowski, adjusted Rand, and percentage of correctly categorized pairings. Experiments conducted on brain tumor gene expression data demonstrate that the techniques used in this study outperform traditional models in terms of stability and biological significance.
The present study was undertaken in order to investigate the role of gentamicin in the gene expression of toxA in Pseudomonas aeruginosa isolated from cow mastitis. A total of ten P. aeruginosa strains originally isolated from cows infected with mastitis. Agar dilution methodology was performed to determine the minimal inhibitory concentration of gentamicin, all of which developed resistance toward gentamicin. The findings presented here demonstrated that all these strains harboured toxA depending on PCR-based assay. Nonetheless, RT-PCR technique revealed a wide variation in expression of toxA. Moreover, the cultivation of P. aeruginosa in the presence of gentamicin, significantly (P< 0.05), induced the expression of toxA, in addition to th
... Show MoreBackground : In order for a tooth to erupt, two obvious requirements are needed. First, there has to be alveolar bone resorption of the bone overlying the crown of the tooth such that an eruption pathway is formed. Second, resorption of bony crypt and apposition of new one, third, there has to be a biological process that will result in the tooth moving through this eruption pathway.The amniotic sac contains a considerable quantity of stem cells. These amniotic stem cells are multipotent and able to differentiate into various tissues, which may be useful for human application. Receptor activator of nuclear factor kappa B ligand (RANKL) is concentrated on bone biology, more specifically bone metabolism. RANKL plays a vital role in osteoclast
... Show MoreBackground: Oral lichen planus (OLP) is a chronic immunologic disease. The etiology of OLP is unknown, viral antigens (for example EBV) have been proposed as etiologic agents. OLP may get transformation to malignancy so research on the presence of these in OLP lesions seems to be necessary. The aim of this study was to evaluate EBV expression immunohistochemically in OLP. Materials and Methods: Tissue specimens of 30 formalin fixed, paraffin-embedded tissue Blocks histologically diagnosed oral lichen planus was performed to evaluate EBV expression. Results: Expression of EBV was detected in epithelium of (46.6%) in the study samples in (OLP). no statistically significant correlation was found with clinical parameters except for a significan
... Show MoreReverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG
... Show MoreAutomatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t
... Show MoreThe current research discusses the topic of the formal data within the methodological framework through defining the research problem, limits and objectives and defining the most important terms mentioned in this research. The theoretical framework in the first section addressed (the concept of the Bauhaus school, the philosophy of the Bauhaus school and the logical bases of this school). The second section dealt with (the most important elements and structural bases of the Bauhaus school) which are considered the most important formal data of this school and their implications on the fabrics and costumes design. The research came up with the most important indicators resulting from the theoretical framework.
Chapter three defined the
Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
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