Article
Biochemical Research Methods
Junyu Long, Shan Huang, Yi Bai, Jinzhu Mao, Anqiang Wang, Yu Lin, Xu Yang, Dongxu Wang, Jianzhen Lin, Jin Bian, Xiaobo Yang, Xinting Sang, Xi Wang, Haitao Zhao
Summary: By employing WGCNA method, this study analyzed gene expression profiles and clinical features of 36 CCA patients, identifying 1478 aberrantly expressed genes in CCA. Seven coexpression modules significantly correlated with clinical traits were identified, with green and blue modules showing significant association with tumor differentiation. Survival analysis revealed 17 hub genes as prognostic biomarkers for CCA patients.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Oncology
Huan Deng, Qingqing Hang, Dijian Shen, Yibi Zhang, Ming Chen
Summary: Our study identified 486 differentially coexpressed genes associated with LUAD, with ten hub genes closely correlated with overall survival. Through functional enrichment analysis and protein-protein interaction network establishment, we found that CHRDL1 and SPARCL1 may serve as potential therapeutic and prognostic indicators for LUAD.
CANCER CELL INTERNATIONAL
(2021)
Article
Multidisciplinary Sciences
Vasileios L. Zogopoulos, Georgia Saxami, Apostolos Malatras, Antonia Angelopoulou, Chih-Hung Jen, William J. Duddy, Gerasimos Daras, Polydefkis Hatzopoulos, David R. Westhead, Ioannis Michalopoulos
Summary: Gene coexpression analysis aims to identify sets of genes with similar expression patterns across multiple data sets, such as microarray experiments. The Arabidopsis Coexpression Tool (ACT) generates a coexpression tree from processed microarray data, revealing relationships between different genes. ACT offers a user-friendly interface for gene set enrichment analysis and is successful in identifying both ubiquitous and tissue-specific gene expressions.
Article
Cell Biology
Vasileios L. Zogopoulos, Apostolos Malatras, Konstantinos Kyriakidis, Chrysanthi Charalampous, Evanthia A. Makrygianni, Stephanie Duguez, Marianna A. Koutsi, Marialena Pouliou, Christos Vasileiou, William J. Duddy, Marios Agelopoulos, George P. Chrousos, Vassiliki A. Iconomidou, Ioannis Michalopoulos
Summary: HGCA2.0 is a webtool that studies the global coexpression of human genes. It analyzes a large-scale dataset of healthy individuals' RNA samples and presents coexpressed subclades to the gene of interest, providing various enrichments analysis on gene ontologies, biological pathways, protein families, and diseases, as well as revealing enriched transcription factors. It has been successful in identifying genes with ubiquitous and tissue-specific expression patterns.
Article
Oncology
Fengwei Li, Qinjunjie Chen, Yang Yang, Meihui Li, Lei Zhang, Zhenlin Yan, Junjie Zhang, Kui Wang
Summary: In this study, 1019 DEGs were filtered to construct four coexpression modules. The red module, which showed the highest correlations with iCCA patients' recurrence status, family history, and day to death, was identified as the key module. Genes in the key module were enriched in genes and pathways related to tumorigenesis and tumor progression. Validation studies revealed estrogen receptor 1 (ESR1) as the real hub gene associated with iCCA recurrence, playing a critical role in suppressing iCCA progression.
CANCER CELL INTERNATIONAL
(2021)
Article
Multidisciplinary Sciences
Soudeh Ghafouri-Fard, Arash Safarzadeh, Mohammad Taheri, Elena Jamali
Summary: A co-expression network of differentially expressed genes (DEGs) related to colorectal cancer (CRC) and their target genes was constructed using the weighted gene co-expression network analysis (WGCNA) algorithm. GO and KEGG pathway analysis revealed that these genes were mainly involved in the regulation of hormone levels, extracellular matrix organization, and extracellular structure organization. The study also identified DKC1, PA2G4, LYAR and NOLC1 as the key hub genes of CRC.
SCIENTIFIC REPORTS
(2023)
Article
Agronomy
Hongli Dong, Lei Yang, Yilin Liu, Guifu Tian, Huan Tang, Shuangshuang Xin, Yixin Cui, Qing Xiong, Huafang Wan, Zhi Liu, Christian Jung, Wei Qian
Summary: This study constructed a gene coexpression network in the early developmental stage of rapeseed seeds and identified gene modules related to seed weight regulation. A key gene, SCPL19, was found through candidate gene association analysis and functionally investigated using Arabidopsis. The study expands our understanding of the molecular mechanism for seed weight regulation in rapeseed.
Article
Biochemistry & Molecular Biology
Qixin Guo, Qiang Qu, Luyang Wang, Shengen Liao, Xu Zhu, Anning Du, Qingqing Zhu, Iokfai Cheang, Rongrong Gao, Xinli Li
Summary: This study aimed to explore the molecular mechanisms of DCM and identify potential gene biomarkers. Four hub genes were identified as potential biomarkers for DCM. The findings have significant implications for the diagnosis and treatment of DCM.
FRONTIERS IN BIOSCIENCE-LANDMARK
(2022)
Article
Veterinary Sciences
Baohong Liu, Xueting Ma, Jianping Cai
Summary: In this study, gene coexpression network analysis was used to identify modules associated with Eimeria tenella infection in chickens, revealing diverse functions such as immune response and metabolism. The findings suggest that infections with different Eimeria species elicit similar biological responses in chickens at the system level.
FRONTIERS IN VETERINARY SCIENCE
(2021)
Article
Oncology
Yanyan Wang, Kang Cui, Mingzhi Zhu, Yuanting Gu
Summary: This study analyzed the RNA-Sequencing and clinical data of breast cancer patients from TCGA database using the weighted gene coexpression network analysis (WGCNA) method. They identified coexpression modules related to breast cancer and discovered potential prognostic biomarkers.
CANCER BIOTHERAPY AND RADIOPHARMACEUTICALS
(2022)
Article
Cardiac & Cardiovascular Systems
Weikang Bian, Zhicheng Wang, Xiaobo Li, Xiao-Xin Jiang, Hongsong Zhang, Zhizhong Liu, Dai-Min Zhang
Summary: In this study, weighted gene coexpression network analysis (WGCNA) was used to identify the key module and hub genes for heart failure (HF). Differential gene expression analysis, coexpression network construction, functional enrichment analysis, and protein-protein interaction network construction were conducted to identify potential hub genes. The results may provide potential biomarkers for the diagnosis of HF and enhance our understanding of the molecular mechanisms underlying HF.
Article
Biotechnology & Applied Microbiology
Zhinan Lin, Yuqi Huang, Sihan Liu, Qiwen Huang, Biliang Zhang, Tianpeng Wang, Ziding Zhang, Xiaowei Zhu, Chenghong Liao, Qian Han
Summary: In this study, a gene coexpression network was constructed to explore the ontogeny of Ae. aegypti. Six gene modules and their intramodular hub genes associated with various developmental processes were identified. These findings provide valuable insights into potential molecular targets for disease control.
Article
Biochemical Research Methods
Yan Guo, Hui Yu, Haocan Song, Jiapeng He, Olufunmilola Oyebamiji, Huining Kang, Jie Ping, Scott Ness, Yu Shyr, Fei Ye
Summary: The MetaGSCA tool allows for comprehensive meta-analyses of gene set differential coexpression data, identifying relevant pathways and visualizing them. The tool demonstrated its effectiveness in case studies of chronic kidney disease and non-small cell lung cancer, as well as in a pan-cancer analysis of 11 cancer types. Analysis with randomly generated gene sets showed low false positive rates, indicating the tool's specificity.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Medicine, Research & Experimental
Zhenyuan Han, Huiping Ren, Jingjing Sun, Lihui Jin, Qin Wang, Chuanbin Guo, Zhen Tian
Summary: This study utilized WGCNA to construct a gene coexpression network for IMPA and identified FZD2 as a central gene associated with the clinical malignancy of IMPA. The expression dynamic of FZD2 correlates negatively with the histological grade of IMPA and serves as a promising histological indicator for the precise prediction of IMPA stages.
JOURNAL OF TRANSLATIONAL MEDICINE
(2022)
Article
Physiology
Biyun Teng, Chaozheng Xie, Yu Zhao, Qiu Zeng, Fangbiao Zhan, Yangyang Feng, Zhe Wang
Summary: This study aims to explore the potential molecular mechanisms and effective targeted therapies for preventing and delaying abdominal aortic aneurysm (AAA) rupture. Through analysis of gene expression data and drug databases, the study identified hypoxic molecules associated with AAA rupture and predicted related traditional Chinese medicine candidates.
FRONTIERS IN PHYSIOLOGY
(2022)
Article
Multidisciplinary Sciences
Jiaxin Li, Ying Li, Pei-Chao Cao, Minghong Qi, Xu Zheng, Yu-Gui Peng, Baowen Li, Xue-Feng Zhu, Andrea Alu, Hongsheng Chen, Cheng-Wei Qiu
Summary: The reciprocity principle governs the symmetry in transmission of electromagnetic and acoustic waves, as well as the diffusion of heat. Recent interest in materials with time-modulated properties has shown efficient breaking of reciprocity for various forms of diffusion. However, time modulation may not be a viable approach to break thermal reciprocity. Our theoretical framework and experimental demonstration highlight the generally preserved nature of thermal reciprocity in dynamic materials.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Gazendra Shakya, Tao Yang, Yu Gao, Apresio K. Fajrial, Baowen Li, Massimo Ruzzene, Mark A. Borden, Xiaoyun Ding
Summary: This study demonstrates the manipulation of internal structure of disk-in-sphere endoskeletal droplets using acoustic wave. The authors developed a model to investigate the physical mechanisms behind this phenomenon and found that the disk orientation can be adjusted reversibly with the frequency of the acoustic driving. This dynamic behavior may provide a pathway for directed assembly of novel hierarchical colloidal architectures and intracellular organelles or intra-organoid structures.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Mate Tibor Veszeli, Gabor Vattay
Summary: The Ising model, which lacks strictly defined dynamics, can be equipped with time dependence through methods such as the Glauber or Kawasaki dynamics. This paper focuses on investigating the temperature dependence of the relaxation time in a Glauber-type master equation, specifically in the case of the fully connected and uniform Ising model. Finite-size effects are analyzed using a reduced master equation, while the thermodynamic limit is examined with a time-dependent mean field equation.
Review
Physics, Multidisciplinary
Jie Chen, Xiangfan Xu, Jun Zhou, Baowen Li
Summary: Interfacial thermal resistance (ITR) is a major obstacle for heat transfer between materials, and understanding it is crucial for efficient heat dissipation in electronic and photonic devices, batteries, etc. This comprehensive review examines ITR, focusing on theoretical, computational, and experimental developments over the past 30 years. It covers fundamental theories, computational methods, and experimental tools for probing ITR, as well as challenges and opportunities in studying nanoscale and atomic scale interfaces.
REVIEWS OF MODERN PHYSICS
(2022)
Article
Agriculture, Dairy & Animal Science
Sara Agnes Nagy, Oz Kilim, Istvan Csabai, Gyorgy Gabor, Norbert Solymosi
Summary: Body condition scoring of dairy cattle is crucial but time-consuming. This study explores the use of computer vision-based deep learning to automate the scoring process. Trained neural networks achieved similar or better results compared to expert scoring, and the pretrained models are freely available for further research.
Article
Mathematics, Applied
Priyanka Rajwani, Ayushi Suman, Sarika Jalan
Summary: Phase transitions are common in natural systems. Incorporating higher-order interactions restores second-order phase transitions and generates tiered synchronization through a combination of super-critical pitchfork and two saddle node bifurcations. The Ott-Antonsen manifold provides a complete description of stable and unstable states and highlights the interplay between higher-order interactions and adaptation in instigating tiered synchronization. These findings are important for understanding the dynamics of real-world systems with inherent higher-order interactions and adaptation through feedback coupling.
Editorial Material
Chemistry, Multidisciplinary
Baowen Li, Jianfang Wang, Tao Deng
Article
Chemistry, Multidisciplinary
Brendan McBennett, Albert Beardo, Emma E. Nelson, Begon Abad, Travis D. Frazer, Amitava Adak, Yuka Esashi, Baowen Li, Henry C. Kapteyn, Margaret M. Murnane, Joshua L. Knobloch
Summary: Nanostructuring allows control over heat flow in semiconductors, but bulk models are limited by boundary effects and first-principles calculations are computationally expensive. We use extreme ultraviolet beams to study phonon transport in a nanostructured silicon metalattice and observe reduced thermal conductivity. We develop a predictive theory that explains this behavior based on nanoscale confinement effects.
Article
Physics, Multidisciplinary
Tanu Raghav, Sarika Jalan
Summary: In this study, eigenvalue ratio statistics of multiplex networks consisting of directed Erdos-Renyi random networks layers represented as weighted non-Hermitian and Hermitian random matrices are analyzed numerically. It is found that the multiplexing strength governs the behavior of average spacing ratio statistics and also affects the eigenvector delocalization of the entire system. These findings contribute to understanding the network properties and the role of multiplexing in dynamical processes of multilayer networks.
NEW JOURNAL OF PHYSICS
(2023)
Article
Mathematics, Interdisciplinary Applications
Vladimir V. Semenov, Sarika Jalan, Anna Zakharova
Summary: In this study, the influence of multiplexing on propagating fronts in multilayer networks of coupled bistable oscillators is investigated using numerical simulation. The results show that multiplexing can reduce the intra-layer dynamics to a common regime, where the front propagation speed in all the interacting layers attains the same fixed value. In the presence of noise, the dynamics become more complicated and the system has the ability to adjust to the common propagation speed by varying the multiplexing strength.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Multidisciplinary Sciences
Laszlo Makrai, Bettina Fodroczy, Sara Agnes Nagy, Peter Czeiszing, Istvan Csabai, Geza Szita, Norbert Solymosi
Summary: This article presents a method for automated counting of bacterial colonies using convolutional neural networks. By culturing 24 bacteria species of veterinary importance and manually annotating 56,865 colonies in a dataset of 369 digital images, it provides a resource for developing artificial intelligence-based approaches to count bacterial colonies.
Article
Veterinary Sciences
Sorin Morariu, Catalin Bogdan Sirbu, Adrienn Greta Toth, Gheorghe Darabus, Ion Oprescu, Narcisa Mederle, Marius Stelian Ilie, Mirela Imre, Beatrice Ana-Maria Sirbu, Norbert Solymosi, Tiana Florea, Kalman Imre
Summary: This study identified the presence of two rumen fluke species in wild ruminants from western Romania, which are highly pathogenic to their hosts. This is the first report of these parasites in deer in Romania.
VETERINARY SCIENCES
(2023)
Article
Physics, Multidisciplinary
Subhasanket Dutta, Omar Alamoudi, Yash Shashank Vakilna, Sandipan Pati, Sarika Jalan
Summary: Quenching of oscillations, an emerging phenomenon in complex systems, is studied using dissimilar couplings and repulsive feedback links in Stuart-Landau oscillators. The conditions for amplitude death are analytically derived, independent of network size, and applicable to nonidentical oscillators. The similarities between this phenomenon and postictal generalized EEG suppression in convulsive seizures are discussed.
PHYSICAL REVIEW RESEARCH
(2023)
Article
Physics, Fluids & Plasmas
Ankit Mishra, Sarika Jalan
Summary: Localization behaviors of Laplacian eigenvectors of complex networks provide explanations for various dynamical phenomena of corresponding complex systems. Through numerical examination, we find that higher-order interactions, even though much fewer than pairwise links, play a key role in steering localization of eigenvectors corresponding to larger eigenvalues. These findings are beneficial for understanding dynamic phenomena in real-world complex systems with higher-order interactions, such as diffusion and random walks.
Article
Multidisciplinary Sciences
Marton Papp, Laszlo Bekesi, Robert Farkas, Laszlo Makrai, Maura Fiona Judge, Gergely Maroti, Dora Tozser, Norbert Solymosi
Summary: The composition of honey bee bacteriota varies depending on climatic and seasonal conditions, and plays a crucial role in their body's functioning.