Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated und

      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

In this work, chemical and thermal treatment were used to enhance silica extract on the purity of rice husk and to reduce the impurities associated with the extraction of silica. The thermal degradation of rice husk was studied. The characteristics and thermal degradation behavior of rice husk which investigated using thermogravimetric analyzer (TGA). Hydrochloric acid was used to soak the rice husk and the study of leaching influence is followed by XRF tests for samples before and after the combustion process. Acid treatment and combustion method seem to have a clear effect on silica purity. The pyrolysis processes were carried out at Laboratory temperature up to 650 oC in the presence of nitrogen gas flowing at 150 ml/min. The effect o

Piroxicam is a non-steroidal anti-inflammatory drug (NSAID) used in the treatment of musculo-skeletal and joint disorders. The problem with this drug is its poor solubility in water and hence poor bioavailability after oral administration. In order to improve its solubility and dissolution behavior, hydrophilic additives such as starch, lactose, superdisintegrants including crospovidone (C.P), cross carmellose sodium (CCS), and sodium starch glycolate (SSG) were physically dry mixed with the drug by simple trituration. The improvement in the solubility in 0.1 N HCl was obtained as the amount of starch or lactose increased in the physical mixture, while for superdisintegrants, they further improve the solubility when they are present in s

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD