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Network Analysis Resources & Updates

Network Analysis Resources & Updates

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📄 Network-based multi-omics integrative analysis methods in drug discovery: a systematic review 📗 Journal: BioData Mining (
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📄 Network-based multi-omics integrative analysis methods in drug discovery: a systematic review 📗 Journal: BioData Mining (I.F.=4) 🗓 Publish year: 2025 🧑‍💻Authors: Wei Jiang, Weicai Ye, Xiaoming Tan, ... 🏢Universities: Hubei University- Sun Yat-sen University, China 📎 Study the paper ⚡️Channel: @ComplexNetworkAnalysis #review #network #multi_omics #drug

📃A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends 🗓 Publ
📃A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends 🗓 Publish year: 2024 📘Journal: Mechanical Systems and Signal Processing(I.F=7.9) 🧑‍💻Authors: Yucheng Wang, Min Wu, Xiaoli Lia, Lihua Xie and Zhenghua Chen 🏢Universities: Nanyang Technological University, Singapore 📎 Study paper 📱Channel: @ComplexNetworkAnalysis #paper #GNN #prediction #Remaining #Life #future #Survey

📚 A Simple Introduction to Graph Theory 💥Booklet 🗓Publish year: 2024 🧑‍💻Author: Brian Heinold 🏢University: Mount Saint
📚 A Simple Introduction to Graph Theory 💥Booklet 🗓Publish year: 2024 🧑‍💻Author: Brian Heinold 🏢University: Mount Saint Mary's University, USA 🌐 Study ⚡️Channel: @ComplexNetworkAnalysis #book #booklet #graph

📃A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions 📕 Journal:IEEE Transactions on Know
📃A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions 📕 Journal:IEEE Transactions on Knowledge and Data Engineering (I.F.=8.9) 🗓 Publish year: 2025 🧑‍💻Authors: Zemin Liu; Yuan Li; Nan Chen, ... 🏢Universities: National University of Singapore 📎 Study the paper 📦 Github 💥 Early access ⚡️Channel: @ComplexNetworkAnalysis #review #imbalanced #learning #graph

Repost from Bioinformatics
📄Graph neural networks for single-cell omics data: a review of approaches and applications 📙 Journal: Briefings in Bioinfor
📄Graph neural networks for single-cell omics data: a review of approaches and applications 📙 Journal: Briefings in Bioinformatics (I.F.=6.8) 🗓 Publish year: 2025 🧑‍💻Authors: Sijie Li, Heyang Hua, Shengquan Chen 🏢Universities: Nankai University, China 📎 Study the paper 📲Channel: @Bioinformatics #review #gnn #single_cell #omic

Repost from Bioinformatics
📃 Biological Multi-Layer and Single Cell Network-Based Multiomics Models - a Review 🗓 Publish year: 2025 🧑‍💻Authors: Marc
📃 Biological Multi-Layer and Single Cell Network-Based Multiomics Models - a Review 🗓 Publish year: 2025 🧑‍💻Authors: Marcello Barylli, Joyaditya Saha, Tineke E. Buffart , ... 🏢Universities: University of Amsterdam - Amsterdam University Medical Centers - Oncode Institute, Netherlands 📎 Study the paper 📲Channel: @Bioinformatics #review #multiomics #network #multi_layer #single_cell

🎞 Introduction to Social Network Analysis 💥This session is part of the ESRC Centre for Society and Mental Health's Research Methods Primer and Provocation series. 💥In this session, Dr Molly Copeland and Holly Crudgington provide an introduction to social network analysis (SNA) with a focus on major theories and conceptual approaches to using ego-centric and sociometric network data for those new to considering networks. 📽 Watch 📱Channel: @ComplexNetworkAnalysis #video

📃Information diffusion analysis: process, model, deployment, and application 📗 Journal:The Knowledge Engineering Review (I.
📃Information diffusion analysis: process, model, deployment, and application 📗 Journal:The Knowledge Engineering Review (I.F.=2.8) 🗓 Publish year: 2025 🧑‍💻Authors: Shashank Sheshar Singh, Divya Srivastava, Madhushi Verma, ... 🏢Universities: Thapar Institute of Engineering & Technology, Bennett University, India 📎 Study the paper ⚡️Channel: @ComplexNetworkAnalysis #review #explainability #gnn

📘 Introduction to Random Graphs 💥 Free online book by Carnegie Mellon University, 2025 🌐 Study ⚡️Channel: @ComplexNetworkA
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📘 Introduction to Random Graphs 💥 Free online book by Carnegie Mellon University, 2025 🌐 Study ⚡️Channel: @ComplexNetworkAnalysis #book #graph #random

📃Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook 🗓 Publish year: 2025 🧑‍💻Authors:
📃Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook 🗓 Publish year: 2025 🧑‍💻Authors: Jiawei Xue, Ruichen Tan, Jianzhu Ma, Satish V. Ukkusuri 🏢Universities: Purdue University, West Lafayette, IN, USA. Tsinghua University, Beijing, China. 📎 Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Data_Mining #Transportation #GNN #review

Repost from Bioinformatics
📃 Graph Neural Network-Based Approaches to Drug Repurposing: A Comprehensive Survey 🗓 Publish year: 2025 🧑‍💻Authors: Alir
📃 Graph Neural Network-Based Approaches to Drug Repurposing: A Comprehensive Survey 🗓 Publish year: 2025 🧑‍💻Authors: Alireza A.Tabatabaei, Mohammad Ebrahim Mahdavi, Ehsan Beiranvand, ... 🏢Universities: University of Isfahan, Shahid Beheshti University of Medical Sciences, University of Tehran - Iran 📎 Study the paper 📲Channel: @Bioinformatics #review #drug #repurposing #gnn

📃A Review of Link Prediction Algorithms in Dynamic Networks 📗 Journal: Mathematics (I.F.=2.3) 🗓 Publish year: 2025 🧑‍💻Au
📃A Review of Link Prediction Algorithms in Dynamic Networks 📗 Journal: Mathematics (I.F.=2.3) 🗓 Publish year: 2025 🧑‍💻Authors: Mengdi Sun, Minghu Tang 🏢Universities: Qinghai Minzu University, China 📎 Study the paper ⚡️Channel: @ComplexNetworkAnalysis #review #explainability #gnn

🎞 Machine Learning with Graphs: GraphSAGE Neighbor Sampling 💥Free recorded course by Prof. Jure Leskovec 💥 This part discussed Neighbor Sampling, That is a representative method used to scale up GNNs to large graphs. The key insight is that a K-layer GNN generates a node embedding by using only the nodes from the K-hop neighborhood around that node. Therefore, to generate embeddings of nodes in the mini-batch, only the K-hop neighborhood nodes and their features are needed to load onto a GPU, a tractable operation even if the original graph is large. To further reduce the computational cost, only a subset of neighboring nodes is sampled for GNNs to aggregate. 📽 Watch 📲Channel: @ComplexNetworkAnalysis #video #course #Graph #GNN #Machine_Learning #GraphSAGE

🎞 Node centrality metric and link analysis 💥Social Network Analysis Lecture 3 📽 Watch 📱Channel: @ComplexNetworkAnalysis #video #Node #centerality #link

📄 A Survey of Graph Transformers: Architectures, Theories and Applications 🗓 Publish year: 2025 🧑‍💻Authors: Chaohao Yuan,
📄 A Survey of Graph Transformers: Architectures, Theories and Applications 🗓 Publish year: 2025 🧑‍💻Authors: Chaohao Yuan, Kangfei Zhao, Ercan Engin Kuruoglu, ... 🏢Universities: Tsinghua University - Chinese University of Hong Kong - Chinese Academy of Sciences, China 📎 Study the paper ⚡️Channel: @ComplexNetworkAnalysis #review #transformer

🎓 Algorithms and Graph Structures for Splitting Network Flows, in Theory and Practice 📕PhD thesis from University of Helsin
🎓 Algorithms and Graph Structures for Splitting Network Flows, in Theory and Practice 📕PhD thesis from University of Helsinki, Finland 🗓Publish year: 2025 📎 Study thesis ⚡️Channel: @ComplexNetworkAnalysis #thesis #network_flow

📃Network link prediction via deep learning method: A comparative analysis with traditional methods 🗓 Publish year: 2024 📘J
📃Network link prediction via deep learning method: A comparative analysis with traditional methods 🗓 Publish year: 2024 📘Journal: Engineering Science and Technology, an International Journal (I.F=5.1) 🧑‍💻Authors: Gholamreza Zare, Nima Jafari Navimipour, Mehdi Hosseinzadeh, Amir Sahafi 🏢Universities: Islamic Azad University, Qeshm Branch, Qeshm, Iran Islamic Azad University, Tabriz Branch, Tabriz, Iran National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan Western Caspian University, Baku, Azerbaijan Duy Tan University, Da Nang, Viet Nam Duy Tan University, School of Medicine and Pharmacy, Da Nang, Viet Nam Islamic Azad University, South Tehran Branch, Tehran, Iran 📎 Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Link_Prediction #Deep_learning #traditional

📑Explaining the Explainers in Graph Neural Networks: a Comparative Study 📕 Journal: ACM Computing Surveys (🔥I.F.=23.8) 🗓
📑Explaining the Explainers in Graph Neural Networks: a Comparative Study 📕 Journal: ACM Computing Surveys (🔥I.F.=23.8) 🗓 Publish year: 2025 🧑‍💻Authors: Antonio Longa, Steve Azzolin, Gabriele Santin, ... 🏢Universities: University of Trento, Italy - Cambridge University, UK 📎 Study the paper ⚡️Channel: @ComplexNetworkAnalysis #review #explainability #gnn

🎥 Knowledge graphs - Foundations and applications 🎞 Watch the collection ⚡️Channel: @ComplexNetworkAnalysis #video #knowled
🎥 Knowledge graphs - Foundations and applications 🎞 Watch the collection ⚡️Channel: @ComplexNetworkAnalysis #video #knowledge_graph

📃A Survey of Large-scale Complex Information Network Representation Learning Methods 🗓 Publish year: 2023 📘Conference: Consumer Electronics and Computer Engineering (ICCECE) 🧑‍💻Authors: Xiaoxian Zhang 🏢Universities: School of Computer Technology and Engineering Changchun Institute of Technology, Changchun, China 📎 Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Large_scale #Complex #Information #Representation_Learning #survey