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| 日期 | 订阅者增长 | 提及 | 频道 | |
| 05 十一月 | +1 | |||
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频道帖子
📃 Artificial Intelligence–Driven Graph Methods for Microbiome Research: A Systematic Review
📘 Journal: WIREs Mechanisms of Disease (I.F. = 5.4)
🗓 Publish year: 2026
🧑💻 Authors: Cedrique Shum-Tim, Paromita Islam, Jacqueline L. Boyajian, Ahmed Abosalha, ...
🏢 Universities: McGill University, Canada
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #microbiome #AI #graph_neural_networks #gnn
| 2 | 📽 Graph Theory for Visual Learners
🎞 Watch
⚡️Channel: @ComplexNetworkAnalysis
#video #basics | 288 |
| 3 |  +2📄 From graphs to qubits: a critical review of quantum graph neural networks
📕 Journal: Neural Computing and Applications (I.F.=4.5)
🗓 Publish year: 2026
🧑💻 Authors: Andrea Ceschini, Francesco Mauro, Francesca De Falco, Alessandro Sebastianelli, ...
🏢Universities: University of Rome “La Sapienza” & University of Sannio & European Space Agency, Italy
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #qubits #gnn | 544 |
| 4 |  📃 A Review and Experimental Analysis of Supervised Learning Systems and Methods for Protein–Protein Interaction Detection
📕 Journal: International Journal of Molecular Sciences (I.F. = 5.6)
🗓 Publish year: 2026
🧑💻 Author: Kamal Taha
🏢 Affiliations: Khalifa University, United Arab Emirates
📎 Study the paper
📲 Channel: @Bioinformatics
#review #machinelearning #proteomics #PPI | 338 |
| 5 |  +1📑 Graph designs for deep learning–based multi-omics integration
📓 Journal: Briefings in Bioinformatics (I.F.=7.3)
🗓 Publish year: 2026
🧑💻Authors: Muhtasim Noor Alif, Khandakar Tanvir Ahmed, Sudipto Baul, Wei Zhang
🏢University: University of Central Florida, USA
📎 Study the paper
📲Channel: @Bioinformatics
#review #multiomics #graph #gnn #deeplearning | 389 |
| 6 |  📃 A Survey on GNN-Based Link Prediction: Techniques, Applications, and Challenges
📔 Journal: WIREs Data Mining and Knowledge Discovery (I.F.=15)
🗓 Publish year: 2026
🧑💻Authors: Chengcheng Sun, Yajie Song, Cheng Zhai, Jiayun Tian, Jia Yang, Xiaobin Rui, Jian Zhang, Zhixiao Wang, Philip S. Yu
🏢Universities: China University of Mining and Technology, China – University of Illinois Chicago, USA
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #link_prediction #gnn | 450 |
| 7 |  +1📑 A Comprehensive Survey on Identifying Influential Nodes: From Structural Centrality-based to Learning-based Methods
📘 Journal: ACM Computing Surveys (🔥I.F.=30.4)
🗓 Publish year: 2026
🧑💻 Authors: Amir Sheikhahmadi, Laleh Tafakori, Mahdi Jalili
🏢 University: RMIT University, Melbourne, Australia
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #influential_node | 484 |
| 8 | 📃 From prior knowledge to data-informed models: a review of Boolean network inference
📓 Journal: Briefings in Bioinformatics (I.F.=7.7)
🗓 Publish year: 2026
🧑💻 Authors: Pierre Klemmer, Ahmed Abdelmonem Hemedan, Reinhard Schneider, Marek Ostaszewski
🏢 Universities: University of Luxembourg – Luxembourg Centre for Systems Biomedicine (LCSB) & Luxembourg Institute of Health (LIH), Luxembourg
📎 Study the paper: https://doi.org/10.1093/bib/bbag499
⚡️Channel: @ComplexNetworkAnalysis
#review #systemsbiology #boolean_network | 3 097 |
| 9 | 📹 Graph Reconstruction
🎞 Watch
⚡️Channel: @ComplexNetworkAnalysis
#video #graph #reconstruction | 443 |
| 10 |  📑 Explainable AI for Graph-Based Learning: A Survey Beyond Graph Neural Networks
🗓 Publish year: 2026
🧑💻Authors: Margarita Bugueño, Russa Biswas, Gerard de Melo
🏢Universities: Hasso Plattner Institute (HPI) / University of Potsdam, Germany - Aalborg University, Denmark
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #explainable #ai #gnn | 532 |
| 11 |  📃 Multilayer public transport networks
🗓 Publish year: 2026
🧑💻 Authors: Tina Šfiligoj, Renzo Massobrio, Oded Cats
🏢 Universities: University of Ljubljana, Slovenia — University of Antwerp, Belgium — Delft University of Technology, The Netherlands
🔍 Highlights: A structured review of multilayer network approaches in public transportation, including network modelling, resilience analysis, service planning, and a proposed taxonomy and research agenda for future research.
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #multilayer #transportation | 581 |
| 12 |  📚 Network model selection: A review of methods
🏛Publisher: Springer Nature — SpringerBriefs
🗓 Publication year: 2026
🧑💻Author: Zoran Levnajić
🏢Affiliation: Faculty of Information Studies in Novo mesto, Slovenia
🔍 This review provides a systematic overview of methods for selecting the network model that best explains a given complex network. It categorizes existing approaches, discusses their principles and software availability, and highlights future directions in network model selection.
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #analysis #model | 566 |
| 13 |  +1📄 A Primer on Bayesian Neural Networks: Review and Debates
📙 Journal: Statistical Science (Impact Factor: 2.32)
🗓 Publish year: 2026
🧑💻Authors: Julyan Arbel, Konstantinos Pitas, Mariia Vladimirova, ...
🏢Universities: Centre Inria de l’Universit´e Grenoble Alpes & Criteo AI Lab, France - Helmholtz AI, Munich, Gremany
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #bayesian #neural_network | 538 |
| 14 |  📃 Graph-based drug–target interaction modeling: from representation learning to output-driven drug discovery
📗 Briefings in Bioinformatics (Impact Factor: 7.3, Q1)
🗓 2026
🧑💻 Thanh Nguyen , Hien Minh To , Duy Anh Nguyen ,...
🏢 Nanyang Biologics, Singapore
📎 Study the paper
⚡️ @ComplexNetworkAnalysis
#review #drug_target #bipartite | 2 928 |
| 15 | 📹 Graph Theory Workshop
🎞 Watch
⚡️ @ComplexNetworkAnalysis
#video #graph | 554 |
| 16 |  📄 Graph Contrastive Learning: A Comprehensive Review of Methodologies, Applications, and Future Directions
📕 IEEE Access (Impact Factor: 4.2, Q2)
🗓 2026
🧑💻 Nazmul Hossain, Abdullah Al Thaki, Md. Mamun-Or-Rashid, Md. Mosaddek Khan
🏢 University of Dhaka, Bangladesh
📎 Study the paper
⚡️ @ComplexNetworkAnalysis
#review #ContrastiveLearning #GNN #SelfSupervisedLearning #GraphNeuralNetworks #RepresentationLearning #MachineLearning | 539 |
| 17 | 📹 Graph Engineering
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⚡️Channel: @ComplexNetworkAnalysis
#video #graph_engineering | 566 |
| 18 |  📃 Introduction to Graph Neural Networks for Machine Learning Engineers
📘 Journal: IEEE Access (I.F.=3.6)
🗓 Publish year: 2026
🧑💻Authors: James Tanis, Chris Giannella, Adrian Mariano, ...
🏢Universities: The MITRE Corporation - National Cancer Institute Shady Grove Campus, United States
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #graph_neural_network #machine_learning | 502 |
| 19 |  +4📄 Graph Neural Networks Applications Across Domains: All Insights You Need
📕 Journal: arXiv preprint (not yet peer-reviewed)
🗓 Publish year: 2026
🧑💻Authors: Abderaouf Bahi
🏢University: Chadli Bendjedid University of El Tarf, Algeria
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#GNN #GraphNeuralNetworks #Survey | 629 |
| 20 |  📑 A review on the use of complex networks in science education research
🗓 Publish year: 2026
🧑💻Authors: Paula Tuz´on, Juan Garc´ıa-Castillo, and Juan Fern´andez-Gracia
🏢University: Universidad de Valencia, Spain
📎 Study the paper
⚡️Channel: @ComplexNetworkAnalysis
#review #science #education | 624 |
