Mujeebu Rehman¹, Qinghua Liu¹, Ali Ghulam², Tariq Ahmad³, Jawad Khan^4,*, Dildar Hussain^5,*, Yeong Hyeon Gu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 779-805, 2025, DOI:10.32604/cmes.2025.067412 - 30 October 2025

Abstract Identifying druggable proteins, which are capable of binding therapeutic compounds, remains a critical and resource-intensive challenge in drug discovery. To address this, we propose CEL-IDP (Comparison of Ensemble Learning Methods for Identification of Druggable Proteins), a computational framework combining three feature extraction methods Dipeptide Deviation from Expected Mean (DDE), Enhanced Amino Acid Composition (EAAC), and Enhanced Grouped Amino Acid Composition (EGAAC) with ensemble learning strategies (Bagging, Boosting, Stacking) to classify druggable proteins from sequence data. DDE captures dipeptide frequency deviations, EAAC encodes positional amino acid information, and EGAAC groups residues by physicochemical properties to generate… More >

YUFENG WANG¹, HUIFENG DANG¹, QIANQIAN WANG¹, SHUXIAO WU¹, LEI HAN¹, XU LUO¹, YINGXIA TIAN^1,*, HAILIN TANG^2,*

Oncology Research, Vol.33, No.8, pp. 1861-1874, 2025, DOI:10.32604/or.2025.063716 - 18 July 2025

Abstract This review focuses on the metabolic issues related to mitochondrial pyruvate dehydrogenase phosphatase (PDP) in malignant tumors and its potential mechanisms. Recent research on tumor metabolic mechanisms has shown that PDP dysregulation is closely linked to metabolic reprogramming in tumor cells, and potentially promotes tumor. Research has comprehensively explored the structural-functional characteristics of PDP, its metabolic regulatory mechanisms, and its role in various types of malignant tumors. Nevertheless, several questions still exist regarding its potential mechanisms within acetylation, phosphorylation, hypoxia, immune infiltration, mitochondrial metabolism, drug resistance, oxidative phosphorylation, and tumor prognosis. This article intends to More >

Talal H. Noor^*

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1273-1299, 2024, DOI:10.32604/csse.2024.052510 - 13 September 2024

Abstract In recent years, container-based cloud virtualization solutions have emerged to mitigate the performance gap between non-virtualized and virtualized physical resources. However, there is a noticeable absence of techniques for predicting microservice performance in current research, which impacts cloud service users’ ability to determine when to provision or de-provision microservices. Predicting microservice performance poses challenges due to overheads associated with actions such as variations in processing time caused by resource contention, which potentially leads to user confusion. In this paper, we propose, develop, and validate a probabilistic architecture named Microservice Performance Diagnosis and Prediction (MPDP). MPDP… More >

Bin Li^*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.10, pp. 2729-2748, 2023, DOI:10.32604/fdmp.2023.029649 - 25 June 2023

Abstract In order to overcome the deficiencies of current methods for the prediction of the productivity of shale gas horizontal wells after fracturing, a new sophisticated approach is proposed in this study. This new model stems from the combination several techniques, namely, artificial neural network (ANN), particle swarm optimization (PSO), Imperialist Competitive Algorithms (ICA), and Ant Clony Optimization (ACO). These are properly implemented by using the geological and engineering parameters collected from 317 wells. The results show that the optimum PSO-ANN model has a high accuracy, obtaining a R² of 0.847 on the testing. The partial dependence More >

Abeer I. Alhujaylan^{1, 2, *}, Manar I. Hosny¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1025-1051, 2020, DOI:10.32604/cmc.2020.08742

Abstract Mobile commerce (m-commerce) contributes to increasing the popularity of electronic commerce (e-commerce), allowing anybody to sell or buy goods using a mobile device or tablet anywhere and at any time. As demand for e-commerce increases tremendously, the pressure on delivery companies increases to organise their transportation plans to achieve profits and customer satisfaction. One important planning problem in this domain is the multi-vehicle profitable pickup and delivery problem (MVPPDP), where a selected set of pickup and delivery customers need to be served within certain allowed trip time. In this paper, we proposed hybrid clustering algorithms More >