Forwarded from Bioinformatics
📑 Enhancing Molecular Network-Based Cancer Driver Gene Prediction Using Machine Learning Approaches: Current Challenges and Opportunities
📓 Journal: Journal of Cellular and Molecular Medicine (I.F.=4.3)
🗓Publish year: 2025
🧑💻Authors: Hao Zhang, Chaohuan Lin, Ying'ao Chen, ...
🏢Universities: Wenzhou Medical University - University of Chinese Academy of Sciences, China
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📲Channel: @Bioinformatics
#review #cancer #network #driver_gene #machine_learning
📓 Journal: Journal of Cellular and Molecular Medicine (I.F.=4.3)
🗓Publish year: 2025
🧑💻Authors: Hao Zhang, Chaohuan Lin, Ying'ao Chen, ...
🏢Universities: Wenzhou Medical University - University of Chinese Academy of Sciences, China
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📲Channel: @Bioinformatics
#review #cancer #network #driver_gene #machine_learning
📃Understanding When and Why Graph Attention Mechanisms Work via Node Classification
🗓Publish year: 2024
🧑💻Authors: Didier A. Vega-Oliveros, Alneu de Andrade Lopes, Lilian Berton
🏢University: Northwestern Polytechnical University, Shanghai Artificial Intelligence Laboratory, Shanghai Jiaotong University
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📲Channel: @ComplexNetworkAnalysis
#Paper #GAT #Attention #node_classification
🗓Publish year: 2024
🧑💻Authors: Didier A. Vega-Oliveros, Alneu de Andrade Lopes, Lilian Berton
🏢University: Northwestern Polytechnical University, Shanghai Artificial Intelligence Laboratory, Shanghai Jiaotong University
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📲Channel: @ComplexNetworkAnalysis
#Paper #GAT #Attention #node_classification
📃A comprehensive survey on graph neural network accelerators
🗓 Publish year: 2025
📘Journal: Frontiers of Computer Science (I.F=3.4)
🧑💻Authors: Jingyu LIU, Shi CHEN, Li SHEN
🏢Universities: School of Computer, National University of Defense Technology, Changsha 410073, China
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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #survey
🗓 Publish year: 2025
📘Journal: Frontiers of Computer Science (I.F=3.4)
🧑💻Authors: Jingyu LIU, Shi CHEN, Li SHEN
🏢Universities: School of Computer, National University of Defense Technology, Changsha 410073, China
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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #survey
📄 A comprehensive bibliometric analysis on social network anonymization: current approaches and future directions
📕 Journal: Knowledge and Information System (I.F.=2.5)
🗓 Publish year: 2025
🧑💻Authors: Navid Yazdanjue, Hossein Yazdanjouei, Hassan Gharoun,...
🏢University:
- University of Technology Sydney, Ultimo, Australia
- Urmia University, Urmia &Iran University of Science and Technology, Iran
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⚡️Channel: @ComplexNetworkAnalysis
#review #anonymization
📕 Journal: Knowledge and Information System (I.F.=2.5)
🗓 Publish year: 2025
🧑💻Authors: Navid Yazdanjue, Hossein Yazdanjouei, Hassan Gharoun,...
🏢University:
- University of Technology Sydney, Ultimo, Australia
- Urmia University, Urmia &Iran University of Science and Technology, Iran
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⚡️Channel: @ComplexNetworkAnalysis
#review #anonymization
👍1
📃A Survey on Graph Neural Networks and its Applications in Various Domains
🗓Publish year: 2025
🧑💻Authors: Tejaswini R. Murgod, P. Srihith Reddy, Shamitha Gaddam, S. Meenakshi Sundaram & C. Anitha
🏢University: BNM Institute of Technology, NITTE Meenakshi Institute of Technology,
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📲Channel: @ComplexNetworkAnalysis
#Paper #Survey #GNN #Application
🗓Publish year: 2025
🧑💻Authors: Tejaswini R. Murgod, P. Srihith Reddy, Shamitha Gaddam, S. Meenakshi Sundaram & C. Anitha
🏢University: BNM Institute of Technology, NITTE Meenakshi Institute of Technology,
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📲Channel: @ComplexNetworkAnalysis
#Paper #Survey #GNN #Application
👍1
📄 Systematic Review of Fake News, Propaganda, and Disinformation: Examining Authors, Content, and Social Impact through Machine Learning
📗 Journal: IEEE ACCESS (I.F.=3.4)
🗓 Publish year: 2025
🧑💻Authors: D. Plikynas, I. Rizgelienė, G. Korvel,...
🏢University: Vilnius university, Vilnius, Lithuania
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⚡️Channel: @ComplexNetworkAnalysis
#review #fake_news
📗 Journal: IEEE ACCESS (I.F.=3.4)
🗓 Publish year: 2025
🧑💻Authors: D. Plikynas, I. Rizgelienė, G. Korvel,...
🏢University: Vilnius university, Vilnius, Lithuania
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#review #fake_news
Forwarded from Bioinformatics
🎬 Inferring Biological Networks
💥 from Claudia Solis-Lemus, Wisconsin Institutes for Discovery, UW-Madison
🎞 Watch
📲Channel: @Bioinformatics
#video #network
💥 from Claudia Solis-Lemus, Wisconsin Institutes for Discovery, UW-Madison
🎞 Watch
📲Channel: @Bioinformatics
#video #network
YouTube
Claudia Solis-Lemus: Inferring Biological Networks
UW-Madison, Wisconsin Evolution, Evolution Seminar Series
https://evolution.wisc.edu/seminars/seminars-info/
https://evolution.wisc.edu
Claudia Solis-Lemus, Assistant Professor, Department of Plant Pathology and Wisconsin Institutes for Discovery, UW-Madison…
https://evolution.wisc.edu/seminars/seminars-info/
https://evolution.wisc.edu
Claudia Solis-Lemus, Assistant Professor, Department of Plant Pathology and Wisconsin Institutes for Discovery, UW-Madison…
Link_Prediction_in_Social_Networks_A_Review.pdf
243.8 KB
📃Link Prediction in Social Networks: A Review
🗓 Publish year: 2024
📘Conference: 2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP)
🧑💻Authors: Meghana Sreeya Veeramallu, Harshitha Reddy Mallu, Ramadasu B
🏢Universities: Chaitanya Bharathi Institute of Technology, India
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📱Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #review
🗓 Publish year: 2024
📘Conference: 2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP)
🧑💻Authors: Meghana Sreeya Veeramallu, Harshitha Reddy Mallu, Ramadasu B
🏢Universities: Chaitanya Bharathi Institute of Technology, India
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📱Channel: @ComplexNetworkAnalysis
#paper #Link_Prediction #review
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🎞 Graph Neural Networks
💥presented by Giannis Nikolentzos at the 2024 HIAS AI Summer School
📽 Watch
📱Channel: @ComplexNetworkAnalysis
#video #GNN
💥presented by Giannis Nikolentzos at the 2024 HIAS AI Summer School
📽 Watch
📱Channel: @ComplexNetworkAnalysis
#video #GNN
YouTube
2024 HIAS AI Summer School - Graph Neural Networks - Giannis Nikolentzos
2024 HIAS AI Summer School Day 1
Graph Neural Networks
Giannis Nikolentzos, University of Patras
Graph Neural Networks
Giannis Nikolentzos, University of Patras
🎞 Machine Learning with Graphs: design space of graph neural networks
💥Free recorded course by Prof. Jure Leskovec
💥 This part discussed the important topic of GNN architecture design. Here, we introduce 3 key aspects in GNN design: (1) a general GNN design space, which includes intra-layer design, inter-layer design and learning configurations; (2) a GNN task space with similarity metrics so that we can characterize different GNN tasks and, therefore, transfer the best GNN models across tasks; (3) an effective GNN evaluation technique so that we can convincingly evaluate any GNN design question, such as “Is BatchNorm generally useful for GNNs?”. Overall, we provide the first systematic investigation of general guidelines for GNN design, understandings of GNN tasks, and how to transfer the best GNN designs across tasks. We release GraphGym as an easy-to-use code platform for GNN architectural design. More information can be found in the paper: Design Space for Graph Neural Networks
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📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning
💥Free recorded course by Prof. Jure Leskovec
💥 This part discussed the important topic of GNN architecture design. Here, we introduce 3 key aspects in GNN design: (1) a general GNN design space, which includes intra-layer design, inter-layer design and learning configurations; (2) a GNN task space with similarity metrics so that we can characterize different GNN tasks and, therefore, transfer the best GNN models across tasks; (3) an effective GNN evaluation technique so that we can convincingly evaluate any GNN design question, such as “Is BatchNorm generally useful for GNNs?”. Overall, we provide the first systematic investigation of general guidelines for GNN design, understandings of GNN tasks, and how to transfer the best GNN designs across tasks. We release GraphGym as an easy-to-use code platform for GNN architectural design. More information can be found in the paper: Design Space for Graph Neural Networks
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning
arXiv.org
Design Space for Graph Neural Networks
The rapid evolution of Graph Neural Networks (GNNs) has led to a growing number of new architectures as well as novel applications. However, current research focuses on proposing and evaluating...
📃Stochastic Block Models for Complex Network Analysis: A Survey
🗓 Publish year: 2024
📘Journal: ACM Transactions on Knowledge Discovery from Data (I.F=4)
🧑💻Authors: Xueyan Liu, Wenzhuo Song, Katarzyna Musial, Yang Li, Xuehua Zhao, Bo Yang
🏢Universities: Jilin University, Northeast Normal University, University of Technology Sydney, Aviation University of Air Force, Shenzhen Institute of Information Technology, Jilin University
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📱Channel: @ComplexNetworkAnalysis
#paper #Stochastic #Block #review
🗓 Publish year: 2024
📘Journal: ACM Transactions on Knowledge Discovery from Data (I.F=4)
🧑💻Authors: Xueyan Liu, Wenzhuo Song, Katarzyna Musial, Yang Li, Xuehua Zhao, Bo Yang
🏢Universities: Jilin University, Northeast Normal University, University of Technology Sydney, Aviation University of Air Force, Shenzhen Institute of Information Technology, Jilin University
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📱Channel: @ComplexNetworkAnalysis
#paper #Stochastic #Block #review
📄 Graph Data Management and Graph Machine Learning: Synergies and Opportunities
🗓 Publish year: 2025
🧑💻Authors: Arijit Kha, Xiangyu Ke, Yinghui Wu
🏢University:
- Aalborg University, Denmark
- Zhejiang University, China
- Case Western Reserve University, USA
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⚡️Channel: @ComplexNetworkAnalysis
#review #graph #machine_learning #data_management
🗓 Publish year: 2025
🧑💻Authors: Arijit Kha, Xiangyu Ke, Yinghui Wu
🏢University:
- Aalborg University, Denmark
- Zhejiang University, China
- Case Western Reserve University, USA
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⚡️Channel: @ComplexNetworkAnalysis
#review #graph #machine_learning #data_management
👍1
📃Counterfactual Learning on Graphs: A Survey
🗓 Publish year: 2025
📘Journal: Machine Intelligence Research
🧑💻Authors: Zhimeng Guo, Zongyu Wu, Teng Xiao, Charu Aggarwal , Hui Liu, Suhang Wang
🏢Universities: Pennsylvania State University, Watson Research Center
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📲Channel: @ComplexNetworkAnalysis
#paper #Counterfactual #Survey
🗓 Publish year: 2025
📘Journal: Machine Intelligence Research
🧑💻Authors: Zhimeng Guo, Zongyu Wu, Teng Xiao, Charu Aggarwal , Hui Liu, Suhang Wang
🏢Universities: Pennsylvania State University, Watson Research Center
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📲Channel: @ComplexNetworkAnalysis
#paper #Counterfactual #Survey
📚 A curated list of awesome network analysis resources
💥 GitBook website
🌐 Study
⚡️Channel: @ComplexNetworkAnalysis
#github #graph #visualization #book
💥 GitBook website
🌐 Study
⚡️Channel: @ComplexNetworkAnalysis
#github #graph #visualization #book
📃Bibliometric and visualized analysis of social network analysis research on Scopus databases and VOSviewer
🗓 Publish year: 2024
📘Journal: Cogent Business & Management (I.F=3)
🧑💻Authors: Dyah gandasari, David tjahjana, Diena Dwidienawati and Mochamad Sugiarto
🏢Universities: Polbangtan Bogor, Bogor, indonesia; universitas Multimedia nusantara, Jakarta, indonesia; Business Management, BinusBusiness school, Bina nusantara university, Jakarta, indonesia; Faculty of animal science, Jendral soedirman university,indonesia
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📱Channel: @ComplexNetworkAnalysis
#paper #Bibliometric #Scopus #VOSviewer
🗓 Publish year: 2024
📘Journal: Cogent Business & Management (I.F=3)
🧑💻Authors: Dyah gandasari, David tjahjana, Diena Dwidienawati and Mochamad Sugiarto
🏢Universities: Polbangtan Bogor, Bogor, indonesia; universitas Multimedia nusantara, Jakarta, indonesia; Business Management, BinusBusiness school, Bina nusantara university, Jakarta, indonesia; Faculty of animal science, Jendral soedirman university,indonesia
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #Bibliometric #Scopus #VOSviewer
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