Mass spectrometry‐based protein–protein interaction networks for the study of human diseases by Alicia L Richards, Manon Eckhardt, Nevan J Krogan

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Application of multilayer network in protein-protein interaction networks (PPI) of rice and cancer by WENG Yuhao, CHEN Ming

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“Infectious uveitis: a comprehensive systematic review of emerging trends and molecular pathogenesis using network analysis” by Muhammad Arif Asghar, Shixin Tang, Li Ping Wong, Peizeng Yang, Qinjian Zhao

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A comprehensive framework of E2–RING E3 interactions of the human ubiquitin–proteasome system by Sjoerd J L van Wijk, Sjoerd J de Vries, Patrick Kemmeren, Anding Huang, Rolf Boelens, Alexandre M J J Bonvin, H Th Marc Timmers

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Single nucleus RNA sequencing profile analysis to reveal cell type specific common molecular drivers of Parkinson’s disease and therapeutic agents by Md. Al Amin Pappu, Md. Alamin, Most. Humaira Sultana, AKM Azad, Md. Rabiul Auwul, Sabkat Mahmud, Alvira Ajadee, Arnob Sarker, Salem A. Alyami, Md. Nurul Haque Mollah

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Proteomic compensation by paralogs preserves protein interaction networks after gene loss in cancer by Anjan Venkatesh, Niall Quinn, Swathi Ramachandra Upadhya, Barbara De Kegel, Alfonso Bolado Carrancio, Thomas Lefeivre, Olivier Dennler, Kieran Wynne, Alexander von Kriegsheim, Colm J Ryan

“…Remarkably, protein–protein interaction networks operating within tumour cells continue to function despite widespread genetic perturbations. …”
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Exploration of the molecular mechanism of melatonin against polycystic ovary syndrome based on a network pharmacology approach and experimental validation by Ran Cheng, Ran Cheng, Ran Cheng, Ying Zhu, Sheng-kai Wang, Chun-Xiao Zong, Hong-Li Zhao, Hong-Li Zhao, Hong-Li Zhao, Qin Zhang, Qin Zhang, Qin Zhang

“…To visualize the relationships between proteins, a protein-protein interaction network was generated using the STRING database. …”
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Clinical and biological significance of estrogen receptor-positive/progesterone receptor-negative in invasive breast cancer: bioinformatic analysis by Maryam Althobiti, Raef Albugami, Mohammed Alnamnakani, Samir Alharbi, Michael Toss, Rajennder Kumar, Fahad Alkhureeb

“…Analysis of the protein-protein interaction networks and gene-gene co-occurrence identified the upregulated hub genes PIP4K2C, CDH1, and CLTC are closely related to key nodes. …”
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Identification and Validation of Autophagy-Related Genes in Primary Ovarian Insufficiency by Gene Expression Profile and Bioinformatic Analysis by Siji Lv, Jiani Sun, Jing Sun

“…Bioinformatics analysis was performed to observe the features of hub genes, including hub gene-RBP/TF/miRNA/drug network construction, functional analysis, and protein-protein interaction network. Pearson’s correlation analysis was also performed to identify the correlation between hub genes and autophagy genes, among which there were four autophagy genes significantly correlated with hub genes, including ATG4B, ATG3, ATG13, and ULK1. …”
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Network pharmacognosy of Galphimia glauca: Mapping the molecular landscape of a traditional Mexican medicinal plant. by María José Cambero Acosta, Guillermo de Anda-Jáuregui

“…Further interaction analysis using STRING-DB generated a dense protein-protein interaction network comprising 1,386 connections. …”
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In Vitro Weight-Loaded Cell Models for Understanding Mechanodependent Molecular Pathways Involved in Orthodontic Tooth Movement: A Systematic Review by Mila Janjic, Denitsa Docheva, Olivera Trickovic Janjic, Andrea Wichelhaus, Uwe Baumert

“…The results are summarized regarding gene expression in relation to force duration and magnitude, and the most significant signaling pathways they take part in are identified using protein-protein interaction networks.…”
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CEN‐tools: an integrative platform to identify the contexts of essential genes by Sumana Sharma, Cansu Dincer, Paula Weidemüller, Gavin J Wright, Evangelia Petsalaki

“…In addition, we integrate the dependency networks with existing protein–protein interaction networks to reveal context‐dependent essential cellular pathways in cancer cells. …”
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Comparative phosphoproteomics provides insights into the differences of porcine longissimus thoracis, semimembranosus, psoas major and semitendinosus muscles by Li Zhang, Wen Luo, Linlin Zhao, Longyun Li, Yizhong Huang

“…A total of 184, 53, 75, and 691 unique DAPPs were identified in LT, SMM, PS, and SMT, respectively. Protein-protein interaction networks revealed that phosphoproteins regulated meat quality differences. …”
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Proteomic analysis of the quality deterioration of pork: a comparative study of fresh and six-month frozen storage by Yajun Shen, Chengyu Ma, Xinxiang Zong, Zhaoqiang Wang, Yang Song, Jian Li

“…Key metabolic pathways, including glycolysis, fatty acid degradation, and oxidative phosphorylation, were notably suppressed in frozen samples. Protein–protein interaction network analysis highlighted central regulatory nodes such as ATP5F1A and CAT, which were downregulated in frozen pork. …”
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Hypoxia-associated genes and metabolic abnormalities in peripheral blood mononuclear cells of type 1 diabetes mellitus patients by Wen-biao Ma, Xue-ying Wang, Yuan-yuan Zuo

“…Functional enrichment analysis, Gene Ontology analysis, and protein–protein interaction network analysis were employed to identify hub genes. …”
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Comparative systems biology of human and mouse as a tool to guide the modeling of human placental pathology by Brian Cox, Max Kotlyar, Andreas I Evangelou, Vladimir Ignatchenko, Alex Ignatchenko, Kathie Whiteley, Igor Jurisica, S Lee Adamson, Janet Rossant, Thomas Kislinger

“…Several of these phenotype‐associated proteins form a tight protein–protein interaction network involving 15 known and 34 novel candidate proteins also likely important in placental structure and/or function. …”
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Transcriptomic Analysis Reveals Candidate Hub Genes and Putative Pathways in <i>Arabidopsis thaliana</i> Roots Responding to <i>Verticillium longisporum</i> Infection by Qiwei Zheng, Yangpujia Zhou, Sui Ni

“…Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on these DEGs. A protein–protein interaction network was constructed using the STRING database. …”
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Identifying novel therapeutic targets for non-alcoholic fatty liver disease using bioinformatics approaches: from drug repositioning to traditional Chinese medicine by Jingmin Zhang, Tianwei Meng, Weiqi Gao, Xinghua Li, Juan Xu

“…Bioinformatics offers a promising approach to identify new targets by analyzing gene expression and drug interactions.ObjectiveThis study aims to identify novel therapeutic targets for NAFLD through bioinformatics, focusing on drug repositioning and traditional Chinese medicine (TCM) components.MethodsThree NAFLD-related gene expression datasets (GSE260666, GSE126848, GSE135251) were analyzed to identify differentially expressed genes. Protein-protein interaction networks were constructed using STRING and visualized with Cytoscape. …”
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Immune molecule diagnostics in colorectal cancer: CCL2 and CXCL11 by Zhang Hui, Xu Baohong, Yin Mengqi, Dong Yan, Lu Mingliang

“…Enrichment analysis of differentially expressed genes (DEGs) was conducted using “clusterProfiler” for Gene Ontology and kyoto encyclopedia of genes and genomes pathways, identifying protein-protein interaction networks to find core hub genes. Notable differences in immune cell infiltration were observed among SSA, TSA, CRC, and healthy tissues, involving various immune cell types. …”
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Integrative bioinformatics analysis and experimental validation of key biomarkers driving the progression of cirrhotic portal hypertension by Meilin Li, Lilin Jiang, Yunrui Ru, Zhonghua Lu, Peng Gu

“…In addition, protein-protein interaction networks and machine learning algorithms were conducted to screen center of candidate genes. …”
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