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Post #1580 155

Forwarded from Bioinformatics

📑 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

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📲Channel: @Bioinformatics
#review #multiomics #graph #gnn #deeplearning
Post #1579 359
📃 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

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⚡️Channel: @ComplexNetworkAnalysis
#review #link_prediction #gnn
  • ❤ 1
Post #1577 430
📑 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

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⚡️Channel: @ComplexNetworkAnalysis
#review #influential_node
  • 🔥 2
  • ❤ 1
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Post #1576 2.9K
📃 From prior knowledge to data-informed models: a review of Boolean network inference

📓 Journal: Briefings in Bioinformatics (I.F.=7.3)
🗓 Publish year: 2026

🧑‍💻 Authors: Pierre Klemmer, Ahmed Abdelmonem Hemedan, Reinhard Schneider, Marek Ostaszewski
🏢 Universities: University of 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
OUP Academic From prior knowledge to data-informed models: a review of Boolean network inference Abstract. Molecular mechanisms are highly complex and involve numerous components in non-linear interactions, imposing challenges in analysis and understan
  • ❤ 1
  • 👍 1
Post #1574 502
📑 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

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⚡️Channel: @ComplexNetworkAnalysis
#review #explainable #ai #gnn
  • 👍 1
Post #1573 591
📃 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.

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⚡️Channel: @ComplexNetworkAnalysis
#review #multilayer #transportation
  • 👍 1
Post #1572 606
📚 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.

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⚡️Channel: @ComplexNetworkAnalysis
#review #analysis #model
  • 👍 2
Post #1570 539
📄 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

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⚡️Channel: @ComplexNetworkAnalysis
#review #bayesian #neural_network
  • ❤ 2
Post #1569 3.23K
📃 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

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⚡️ @ComplexNetworkAnalysis
#review #drug_target #bipartite
  • 🔥 2
  • ❤ 1
Post #1567 662
📄 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

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⚡️ @ComplexNetworkAnalysis
#review #ContrastiveLearning #GNN #SelfSupervisedLearning #GraphNeuralNetworks #RepresentationLearning #MachineLearning
  • ❤ 2
  • 🔥 1
Post #1565 620
📃 Introduction to Graph Neural Networks for Machine Learning Engineers

📘 Journal: ACM Computing Surveys (🔥I.F.=28)
🗓 Publish year: 2026

🧑‍💻Authors: James Tanis, Chris Giannella, Adrian Mariano, ...
🏢Universities: The MITRE Corporation - National Cancer Institute Shady Grove Campus, United States

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⚡️Channel: @ComplexNetworkAnalysis
#review #graph_neural_network #machine_learning
  • ❤ 2
  • 👍 1
Post #1560 722
📄 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
  • 👍 2
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