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Physical interactions between proteins are central to all biological processes. Yet, the current knowledge of who interacts with whom in the cell and in what manner relies on partial, noisy, and highly heterogeneous data. Thus, there is a need for methods comprehensively describing and organizing such data. LEVELNET is a versatile and interactive tool for visualizing, exploring, and comparing protein-protein interaction (PPI) networks inferred from different types of evidence. LEVELNET helps to break down the complexity of PPI networks by representing them as multi-layered graphs and by facilitating the direct comparison of their subnetworks toward biological interpretation. It focuses primarily on the protein chains whose 3D structures are available in the Protein Data Bank. We showcase some potential applications, such as investigating the structural evidence supporting PPIs associated to specific biological processes, assessing the co-localization of interaction partners, comparing the PPI networks obtained through computational experiments versus homology transfer, and creating PPI benchmarks with desired properties.
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http://dx.doi.org/10.1002/pmic.202200159 | DOI Listing |
J Burn Care Res
September 2025
Department of Burn Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Background: Burn injuries trigger complex immune responses and gene expression changes, impacting wound healing and systemic inflammation. Understanding these changes is crucial for identifying biomarkers and therapeutic targets.
Methods: We analyzed two GEO datasets (wound tissue (GSE8056) and blood (GSE37069)) to identify differentially expressed genes (DEGs) in burn injury samples versus controls.
Int J Endocrinol
August 2025
Department of Geriatrics, Zhongshan Hospital Xiamen University, School of Medicine, Xiamen University, Xiamen 361000, Fujian, China.
Osteoporosis is a progressive bone disease characterized by reduced bone density and deterioration of bone microarchitecture, predominantly affecting the elderly population. The ongoing COVID-19 pandemic has introduced additional challenges in osteoporosis management, potentially due to systemic inflammation and direct viral impacts on bone metabolism. This study aims to identify common differentially expressed genes (DEGs) and key molecular pathways shared between osteoporosis and COVID-19, with the goal of uncovering potential therapeutic targets through bioinformatics analysis.
View Article and Find Full Text PDFFront Pharmacol
August 2025
College of Pharmacy, Binzhou Medical University, Binzhou, Shandong, China.
Introduction: Age-related macular degeneration (AMD) is a leading cause of vision loss in older adults, with limited effective treatments available. This study aimed to investigate the pharmacological effects of dihydromyricetin (DHM) on AMD and to identify its putative pharmacological targets through network analysis and molecular docking approaches.
Methods: experiments established an AMD model using sodium iodate (SI)-induced ARPE-19 cells, with CCK-8 assays determining 15 mM SI as the optimal modeling concentration and 100 μM DHM as the optimal treatment concentration.
Oncol Res
September 2025
Department of Pathology, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, 415000, China.
Background: The study aimed to explore the clinical value of mitochondrial ribosomal protein L18 (MRPL18) in breast cancer.
Methods: Multiple databases were used to validate the expression of MRPL18. The prognostic impact and predictive value of MRPL18 were evaluated by using predictive models.
Oncol Res
September 2025
Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Studies have reported the special value of PANoptosis in cancer, but there is no study on the prognostic and therapeutic effects of PANoptosis in bladder cancer (BLCA). This study aimed to explore the role of PANoptosis in BLCA heterogeneity and its impact on clinical outcomes and immunotherapy response while establishing a robust prognostic model based on PANoptosis-related features. Gene expression profiles and clinical data were collected from public databases.
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