Results 261 to 270 of about 100,698 (279)

Mechanisms of Aristolochic Acid Resistance in Specialist Butterflies and Evolutionary Insights for Potential Protective Pathways

Advanced Science, EarlyView.
The study provides an extreme example of insect adaptation to highly toxic defenses of host plants, and investigates the complex strategies to resist carcinogenic aristolochic acids, including physical isolation, metabolic detoxification, and DNA repair.
Yang Luan, Yubo Zhang, Jingjing Li, Jianqing Zhu, Yuyang Lei, Yushi Hu, Zhenqiang Xin, Tianpei Xie, Jiang Zheng, Yuanyuan Lin, Jingjing Shen, Yiyi Cao, Xinyue You, Jing Xi, Jiaying Wu, Weiying Liu, Xinyu Zhang, Yuanting Zheng, David J. Lohman, Leming Shi, Wei Zhang   +20 more
wiley   +1 more source

Inferring Gene Regulatory Networks From Single‐Cell RNA Sequencing Data by Dual‐Role Graph Contrastive Learning

Advanced Science, EarlyView.
RegGAIN is a novel and powerful deep learning framework for inferring gene regulatory networks (GRNs) from single‐cell RNA sequencing data. By integrating self‐supervised contrastive learning with dual‐role gene representations, it consistently outperforms existing methods in both accuracy and robustness.
Qiyuan Guan, Jiating Yu, Jieyi Pan, Fan Yuan, Jiadong Ji, Rusong Zhao, Zhi‐Ping Liu, Bingqiang Liu, Ling‐Yun Wu, Duanchen Sun   +9 more
wiley   +1 more source

NUDT21‐mediated Alternative Polyadenylation of CDK19 Reprograms Cholesterol Biosynthesis to Drive Colorectal Cancer Progression

Advanced Science, EarlyView.
NUDT21 is overexpressed in colorectal cancer tumors and promotes colorectal cancer progression. NUDT21 promotes the production of a cyclin‐dependent kinase 19 (CDK19) mRNA isoform with a long 3′ UTR, which enhances cytoplasmic export and translation. Truncation of the CDK19 long 3′ UTR phenocopies NUDT21 loss, recapitulating the defects in cholesterol ...
Yeping Yu, Jixin Ma, Minwei Zhou, Xiaodong Gu, Yiming Zhou, Zhenyang Li, Tianyu Zhang, Wei Gong, Chuanxin Huang, Jianbin Xiang   +9 more
wiley   +1 more source

SIRT5–RAC2 Axis Drives Monocyte‐to‐Macrophage Differentiation to Promote Inflammatory Injury in Premature Ovarian Insufficiency

Advanced Science, EarlyView.
SIRT5 desuccinylates and stabilizes RAC2, activating CSF1R‐dependent signaling to drive monocyte differentiation into M0 macrophages and their polarization toward pro‐inflammatory M1 phenotypes in CTX‐induced premature ovarian insufficiency. Inhibiting the SIRT5‐RAC2 axis attenuates inflammation, reduces granulosa cell apoptosis, and preserves ...
Wenjing TanTai, Yaqi Li, Shengnan Liu, Minjuan Wu, Zhixiao Liu, Junfeng Jiang, Jingjing Chen, Xiaoding Xu, Li Li, Chaoqun Li, Fang Zhao, Ye Liu, Haitao Ni, Tengfei Zhang, Mingjuan Xu, Chaofeng Han   +15 more
wiley   +1 more source

Identification and Functional Characterization of Upregulated Hub Genes in Adenocarcinoma across Multiple Organ Sites

R. Romero, Dulce M. A. Bastida
openalex   +2 more sources

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Association analysis of hepatocellular carcinoma‐related hub proteins and hub genes

PROTEOMICS – Clinical Applications, 2023
AbstractPurposeHepatocellular 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, Boyan Zhang, Yawei Zhang, Fan Zhang   +3 more
openaire   +2 more sources

RANKING DIFFERENTIAL HUBS IN GENE CO-EXPRESSION NETWORKS

Journal of Bioinformatics and Computational Biology, 2012
Identifying 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
openaire   +2 more sources

Hub Genes Identification in Brain Cancer with Gene Expression Data

2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), 2020
Central nervous system (CNS) cancers are one of the leading cancer types in the world. Analysing gene hubs involved in CNS cancer is important for predicting therapies. We have used gene expression data from one of the common brain cancer type (Pheochromocytoma /paraganglioma (PCPG)) for hub gene identification.
S. P. B. M Senadheera, A. R. Weerasinghe
openaire   +1 more source

Weighted gene co-expression network analysis for hub genes in colorectal cancer

Pharmacological Reports, 2023
This study is designed to explore hub genes participating in colorectal cancer (CRC) development through weighted gene co-expression network analysis (WGCNA).Expression profiles of CRC and normal samples were retrieved from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA), and were subjected to WGCNA to filter differentially ...
Zheng Xu, Jianing Wang, Guosheng Wang
openaire   +2 more sources

Spatial organization of gene expression: the active chromatin hub

Chromosome Research, 2003
Developmental and tissue-specific expression of higher eukaryotic genes involves activation of transcription at the appropriate time and place and keeping it silent otherwise. Unlike housekeeping genes, tissue-specific genes generally do not cluster on the chromosomes.
de Laat, WL (Wouter), Grosveld, Frank
openaire   +3 more sources