In silico evaluation of missense SNPs in cancer-associated Cystatin A protein and their potential to disrupt Cathepsin B interaction by Shafaat Hossain, Omar Hamza Bin Manjur, Mst Sharmin Sultana Shimu, Tamanna Sultana, Mustafizur Rahman Naim, Shahariar Siddique, Abdullah Al Mamun, Md Miftaur Rahman, Md Abu Saleh, Md Rakibul Hasan, Tania Rahman

“…Five mutations (Y43C, Y43N, V48F, Y53H, and E94K) located in the conserved region were found to be highly deleterious and less stabilizing. The protein-protein interaction network found that Cathepsin B (CTSB) interacts highly with CSTA. …”
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Identification of circRNA/miRNA/mRNA regulatory network involving (+)-catechin ameliorates diabetic nephropathy mice by Chao Chen, Dina Zhu, Shuai Zhang, Wensheng Zhang

“…The expanded network of proteins interacting with these 5 genes shows that the TGF-β signaling pathway, signaling pathways regulating pluripotency of stem cell, fat digestion and absorption, and PPAR signaling pathway was highly enriched. …”
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Exploration of interstitial fluid proteome in Homo sapiens forearm through a cutting edge intradermal microdialysis and high-throughput proteomics approach: a pilot study by Yu Sakamoto, Naoto Fujii, Junko Shibato, Ravi Gupta, Cheol Woo Min, Sun Tae Kim, Ranjith Kumar Bakku, Randeep Rakwal

“…Dialysate samples were checked for protein extracted in LB-TT, SDS-PAGE, and by LC–MS/MS. A protein–protein interaction (PPI) network was constructed with genes from STRING using Cytoscape. …”
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CaGe: A Web-Based Cancer Gene Annotation System for Cancer Genomics by Young-Kyu Park, Tae-Wook Kang, Su-Jin Baek, Kwon-Il Kim, Seon-Young Kim, Doheon Lee, Yong Sung Kim

“…The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. …”
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Bioinformatics and System Biological Approaches for the Identification of Genetic Risk Factors in the Progression of Cardiovascular Disease by Joy Dip Barua, Shudeb Babu Sen Omit, Humayan Kabir Rana, Nitun Kumar Podder, Utpala Nanda Chowdhury, Md Habibur Rahman

“…We performed several analyses including gene expression analysis, diseasome analysis, protein-protein interaction (PPI) analysis, and pathway analysis for discovering the relationship between CVD and its risk factors. …”
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The role of SASP in ischemic stroke: a deep dive into cellular mechanisms by Dong Xie, Yang Liu, Fang-Biao Xu, Jin-Sheng Zhang

“…The present study endeavored to preliminarily dissect the SASP-IS nexus via combined bulk and single-cell transcriptome analysis.MethodsAggregated expression profiles from human peripheral blood bulk chips and MCAO mouse single-cell sequencing data, followed by SASP gene analysis. Executed protein interaction network and enrichment assays. Investigated immune infiltration in stroke patients, managed quality control and annotation of single-cell data, cherry-picked central cells based on SASP scores, unearthed essential genes via enrichment analysis, conducted pseudo-time and intercellular communication studies, and prognosticated drugs for hub genes. …”
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CDC25B Is a Prognostic Biomarker Associated With Immune Infiltration and Drug Sensitivity in Hepatocellular Carcinoma by Zixiang Huang, Liangzhi Xu, Zhengqiang Wu, Xiaofeng Xiong, Linfei Luo, Zhili Wen

“…Gene set enrichment analysis (GSEA) was used to identify signaling pathways enriched in CDC25B expression, and differential genes (DEGs) were used to screen out coexpressed hub genes and construct protein-protein interaction (PPI) networks. 5-Ethynyl-2′-deoxyuridine (EDU) staining was used to compare the proliferation and differentiation ability of the HCC cell line (HCC-LM3) after knockdown of CDC25B. …”
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Effects of Baicalin on Gout Based on Network Pharmacology, Molecular Docking, and in vitro Experiments by Liu C, Liu W, Lu H, Fan Y, Wang A

“…Then, the potential targets and signaling pathways were acquired via protein–protein interaction (PPI), as well as the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. …”
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Transcriptomic Analysis of Pathogenicity Genes in Sclerotinia sclerotiorum Affecting Brassica napus by Hengameh Taheri, Mohamad Hamed Ghodoum Parizipour

“…It examines these genes' codon usage bias (CUB) to find the optimal codons effective in gene expression and the factors effective in the formation of CUB. Protein-protein interaction network was drawn and several hub genes were determined and ranked according to the CytoHubba tool among which the genes encoding nitrate reductase, beta-glucosidase, glucanase, PA14 domain-containing protein, carbohydrate-binding module family 1, and acyl-coenzyme A oxidase were found to be associated with the SSR induction. …”
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Bioinformatics analysis combined with experimental validation reveals the biological role of the ILK gene in prostate cancer by Xiao-xiang Yu, Yi Liu, Rong-jiang Luo, Zi-xuan Song, Wen-kai Chen, Zeng-mi Mo, Feng-jing Wang

“…Results 544 significant genes were identified by WGCNA. The protein–protein interaction (PPI) network analysis revealed that MYC was the central regulatory gene, with the intersected genes mainly involved in regulating cell adhesion and drug metabolism in prostate cancer (PCa). …”
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Identification of key genes associated with oxidative stress in ischemic stroke via bioinformatics integrated analysis by Gaiyan Li, Yu Cheng, Shanshan Ding, Qianyun Zheng, Lanqiong Kuang, Ying Zhang, Ying Zhou

“…Subsequently, protein–protein interaction (PPI) network and machine learning algorithms were utilized to excavate feature genes. …”
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Identification and Validation of the Pyroptosis-Related Hub Gene Signature and the Associated Regulation Axis in Diabetic Keratopathy by Yi Cui, Li Wang, Wentao Liang, Li Huang, Shuting Zhuang, Hong Shi, Nuo Xu, Jianzhang Hu

“…An integrated bioinformatics pipeline, including differentially expressed gene (DEG) identification, enrichment analysis, protein-protein interaction (PPI) network, coexpression, drug prediction, and immune deconvolution analyses, identified hub genes and key drivers in DK pathogenesis. …”
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Analysis of differentially expressed genes in hypertension and hypertensive cerebral hemorrhage via RNA-sequencing by Hongwu Qi, Min Qiao, Yansong Liu, Weijun Zeng, Lizhao Zhang, Hongjun Guo

“…Functional annotation and protein–protein interaction (PPI) network construction of HT- and HCH-specific DEGs were conducted. …”
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Identification of biomarkers associated with coronary artery disease and non-alcoholic fatty liver disease by bioinformatics analysis and machine learning by Chuan Lu, Mei Han, Qiqi Ma, Li Ying, Yue Zhang

“…We downloaded CAD and NAFLD datasets from the Gene Expression Omnibus (GEO) database and analyzed the differentially expressed genes (DEGs) by limma. Protein–protein interaction (PPI) network was constructed with common DEGs (co-DEGs), and hub genes were screened by Maximal Clique Centrality (MCC) algorithm. …”
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Identification and validation of key autophagy-related genes in lupus nephritis by bioinformatics and machine learning. by Su Zhang, Weitao Hu, Yelin Tang, Xiaoqing Chen

“…Differentially expressed autophagy-related genes (DE-ARGs) among DEGs, key module genes and autophagy-related genes (ARGs) were obtained by venn plot, and subjected to protein-protein interaction network construction. Two machine learning methods were applied to identify signature genes. …”
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The functional insight into the genetics of cardiovascular disease: results from the post-GWAS study by L. O. Bryzgalov, E. E. Korbolina, I. S. Damarov, T. I. Merkulova

“…Functional pathway enrichment and protein– protein interaction (PPI) network analyses were performed on the targets and the extended genes by STRING and DAVID. …”
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MicroRNA-Based Markers of Oral Tongue Squamous Cell Carcinoma and Buccal Squamous Cell Carcinoma: A Systems Biology Approach by Setareh Shojaei, Pouya Menbari, Shokoofeh Jamshidi, Amir Taherkhani

“…With the use of the STRING database, a protein interaction map (PIM) was created. Using the Cytoscape program, hub genes and clusters within the PIM were shown. …”
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Active Ingredients and Potential Mechanism of Additive Sishen Decoction in Treating Rheumatoid Arthritis with Network Pharmacology and Molecular Dynamics Simulation and Experimenta... by Ren J, Liu Z, Qi X, Meng X, Guo L, Yu Y, Dong T, Li Q

“…Additive Sishen decoction (ASSD) is a widely used traditional Chinese medicine for the treatment of RA; however, its active ingredients and the mechanism of its therapeutic effects remain unclear.Methods: To predict the ingredients and key targets of ASSD, we constructed “drug-ingredient-target-disease” and protein–protein interaction networks. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to explore the potential mechanism. …”
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Investigation of Scutellaria Barbata’s immunological mechanism against thyroid cancer using network pharmacology and experimental validation by Gen Ouyang, Yuangui Zhu, Zhehao Ouyang

“…TC targets were then filtered, and common targets were selected to build a protein-protein interaction network. GO and KEGG enrichment analyses were performed. …”
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Mechanistic insights into epithelial-mesenchymal transition mediated cisplatin resistance in ovarian cancer by Taha Umair Wani, Hyun-Yi Kim, Geum-Hwa Lee, Young Je Lim, Han-Jung Chae, Ji-Ye Kim, Hyonok Yoon

“…This was further confirmed by the protein-protein interaction (PPI) analysis where we identified that the core ECM components e.g., collagen, fibronectin, metalloproteases and integrins possessed most interactions. …”
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