Identification of hub genes in peripheral blood and construction of a diagnostic nomogram model in ulcerative colitis. [PDF]
Li X, Ge L, Zhang Y, Xu H.
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Stage‐Specific H3K14 and H3K23 Succinylation Orchestrates Insect Metamorphosis and Oogenesis
Stage‐specific succinylation of histone H3 at lysine 14 and 23 differentially controls insect metamorphosis and oogenesis through distinct GPCR‐PKC signaling cascades, revealing an evolutionarily conserved epigenetic mechanism that coordinates key life‐history traits.
Yu‐Pu Jing +9 more
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Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction. [PDF]
Zhou L, Chen W, Li J, Chen M.
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Transcriptomic analysis identifies hub genes involved in age-dependent abdominal fat development in chickens. [PDF]
Wei W +8 more
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Identification of Ferroptosis-Related Hub Genes and Immune Infiltration Landscape in Chronic Kidney Disease via Bioinformatics and Experimental Verification. [PDF]
Luo Y, Huang ZY, Yang JF.
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Identification and functional analysis of hub genes in knee osteoarthritis via bioinformatics and experimental validation. [PDF]
Jiang S +7 more
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The analysis reveals novel hub genes and pathways associated with Tetralogy of Fallot. [PDF]
Wen H +5 more
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Multi-omics data mining combined with experimental validation reveals ferroptosis- and autophagy-associated hub genes as diagnostic candidates and immune modulators in atherosclerosis. [PDF]
Zheng X +6 more
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Association analysis of hepatocellular carcinoma‐related hub proteins and hub genes
PROTEOMICS – Clinical Applications, 2023AbstractPurposeHepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation.
Xinhong Zhang +3 more
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RANKING DIFFERENTIAL HUBS IN GENE CO-EXPRESSION NETWORKS
Journal of Bioinformatics and Computational Biology, 2012Identifying the genes that change their expressions between two conditions (such as normal versus cancer) is a crucial task that can help in understanding the causes of diseases. Differential networking has emerged as a powerful approach to detect the changes in network structures and to identify the differentially connected genes among two networks ...
Omar Odibat, Chandan K. Reddy
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