CHAO LIU^*

BIOCELL, Vol.48, No.2, pp. 339-351, 2024, DOI:10.32604/biocell.2023.047044

Abstract Introduction: Osteoarthritis (OA) is still an important health problem, and understanding its pathological mechanisms is essential for its diagnosis and treatment. There is evidence that autophagy may play a role in OA progression, but the exact mechanism remains unclear. Methods: In this study, we adopted a multi-prong approach to systematically identify the key autophagy-related genes (ARGs) associated with OA. Through weighted gene co-expression network analysis, we initially identified significant gene modules associated with OA. Subsequent differential gene analysis performed on normal and OA specimens. Further analysis later using the MCC algorithm highlighted hub ARGs. These genes were then incorporated into… More >

JINFANG HU^1,#, JIANGEN AO^2,#, LONGSHENG FU^1,#, YAOQI WU¹, FENG SHAO³, TIANTIAN XU¹, MINGJIN JIANG⁴, SHAOFENG XIONG¹, YANNI LV^1,*

BIOCELL, Vol.47, No.7, pp. 1611-1622, 2023, DOI:10.32604/biocell.2023.028684

Abstract Background: The attenuation function of Dalbergia odorifera leaves on cerebral ischemia-reperfusion (I/R) is little known. The candidate targets for the Chinese herb were extracted from brain tissues through the high-affinity chromatography. The molecular mechanism of D. odorifera leaves on cerebral I/R was investigated. Methods: Serial affinity chromatography based on D. odorifera leaves extract (DLE) affinity matrices were applied to find specific binding proteins in the brain tissues implemented on C57BL/6 mice by intraluminal middle cerebral artery occlusion for 1 h and reperfusion for 24 h. Specific binding proteins were subjected to mass-spectrometry to search for the differentially expressed proteins between… More >

CAN CHEN^#, RUI FENG^#, ZONGQIONG ZHANG^#, XIUZHONG XIA, BAOXUAN NONG, YU ZENG, HUI GUO, XINGHAI YANG^*, DANTING LI^*

BIOCELL, Vol.47, No.2, pp. 409-421, 2023, DOI:10.32604/biocell.2023.023543

Abstract Plant height (PH) is a complex trait regulated by the environment and multiple genes. PH directly affects crop yield, harvest index, and lodging resistance. From plant dwarf mutants, many genes related to PH have been identified and described. Nonetheless, the molecular mechanism of height regulation in high-culm rice mutants has not been well studied. By using transcriptome and weighted gene co-expression network analysis (WGCNA), we identified the differentially expressed genes (DEGs) between high-culm rice mutants (MUT) and wild-type (WT) and explored the key pathways and potential candidate genes involved in PH regulation. Transcriptome analysis identified a total of 2,184 DEGs,… More >

Ayodeji O. J Ibitoye^1,*, Olufade F. W Onifade²

Journal on Big Data, Vol.4, No.2, pp. 87-95, 2022, DOI:10.32604/jbd.2022.024533

Abstract Community based churn prediction, or the assignment of recognising the influence of a customer’s community in churn prediction has become an important concern for firms in many different industries. While churn prediction until recent times have focused only on transactional dataset (targeted approach), the untargeted approach through product advisement, digital marketing and expressions in customer’s opinion on the social media like Twitter, have not been fully harnessed. Although this data source has become an important influencing factor with lasting impact on churn management. Since Social Network Analysis (SNA) has become a blended approach for churn prediction and management in modern… More >

Farhan Amin, Gyu Sang Choi^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6367-6391, 2022, DOI:10.32604/cmc.2022.029927

Abstract The Internet of Things (IoT) has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses. Social network analysis (SNA) is a good example that has recently gained a lot of scientific attention. It has its roots in social and economic research, as well as the evaluation of network science, such as graph theory. Scientists in this area have subverted predefined theories, offering revolutionary ones regarding interconnected networks, and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon. The motivation of this study is… More >

Xingliang Feng^*1, Meng Zhang^*†1, Jialin Meng^*, Yongqiang Wang^†, Yi Liu^*, Chaozhao Liang^*, Song Fan^*

Oncology Research, Vol.28, No.3, pp. 285-297, 2020, DOI:10.3727/096504020X15791676105394

Abstract We aimed to investigate the potential mechanisms of progression and identify novel prognosis-related biomarkers for papillary renal cell carcinoma (PRCC) patients. The related data were derived from The Cancer Genome Atlas (TCGA) and then analyzed by weighted gene coexpression network analysis (WGCNA). The correlation between each module and the clinical traits were analyzed by Pearson’s correlation analysis. Pathway analysis was conducted to reveal potential mechanisms. Hub genes within each module were screened by intramodule analysis, and visualized by Cytoscape software. Furthermore, important hub genes were validated in an external dataset and clinical samples. A total of 5,839 differentially expressed genes… More >

Pihua Han^*†1, Haiming Yang^‡1, Xiang Li^*1, Jie Wu^*, Peili Wang^§, Dapeng Liu^*, Guodong Xiao^¶, Xin Sun^*, Hong Ren^*

Oncology Research, Vol.28, No.7-8, pp. 715-729, 2020, DOI:10.3727/096504020X16037124605559

Abstract The aim of this study was to identify a novel cancer stemness-related ceRNA regulatory axis in lung adenocarcinoma (LUAD) via weighted gene coexpression network analysis of a stemness index. The RNA sequencing expression profiles of 513 cancer samples and 60 normal samples were obtained from the TCGA database. Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) were identified with R software. Functional enrichment analysis was conducted using DAVID 6.8. The ceRNA network was constructed via multiple bioinformatics analyses, and the correlations between possible ceRNAs and prognosis were analyzed using Kaplan–Meier plots. WGCNA was then applied to distinguish key genes… More >

JUNXIA LIU¹, KE PANG², FEI HE^2,*

BIOCELL, Vol.46, No.7, pp. 1661-1673, 2022, DOI:10.32604/biocell.2022.018023

Abstract Breast cancer is one of the most common cancers in the world and seriously threatens the health of women worldwide. Prognostic models based on immune-related genes help to improve the prognosis prediction and clinical treatment of breast cancer patients. In the study, we used weighted gene co-expression network analysis to construct a co-expression network to screen out highly prognostic immune-related genes. Subsequently, the prognostic immune-related gene signature was successfully constructed from highly immune-related genes through COX regression and LASSO COX analysis. Survival analysis and time receiver operating characteristic curves indicate that the prognostic signature has strong predictive performance. And we… More >

Tengfei Tu^1,2, Wei Yin³, Hua Zhang^1,2,*, Xingyu Zeng¹, Xiaoxiang Deng¹, Yuchen Zhou¹, Xu Liu⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2315-2331, 2022, DOI:10.32604/cmc.2022.022540

Abstract The Internet Control Message Protocol (ICMP) covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission. Its concealment is stronger and it is not easy to be discovered. Most detection methods are detecting the existence of channels instead of clarifying specific attack intentions. In this paper, we propose an ICMP covert tunnel attack intent detection framework ICMPTend, which includes five steps: data collection, feature dictionary construction, data preprocessing, model construction, and attack intent prediction. ICMPTend can detect a variety of attack intentions, such as shell attacks, sensitive directory access,… More >

Mohamed Abdel-Basset¹, Asmaa Atef¹, Mohamed Abouhawwash^2,3, Yunyoung Nam^4,*, Nabil M. AbdelAziz¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1281-1296, 2022, DOI:10.32604/cmc.2022.018947

Abstract The critical path method is one of the oldest and most important techniques used for planning and scheduling projects. The main objective of project management science is to determine the critical path through a network representation of projects. The critical path through a network can be determined by many algorithms and is useful for managing, monitoring, and controlling the time and cost of an entire project. The essential problem in this case is that activity durations are uncertain; time presents considerable uncertainty because the time of an activity is not always easily or accurately estimated. This issue increases the need… More >