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๐ŸŽž Machine Learning with Graphs: Graph Neural Networks in Computational Biology

๐Ÿ’ฅFree recorded course by Prof. Marinka Zitnik

๐Ÿ’ฅIn this lecture, Prof. Marinka gives an overview of why graph learning techniques can greatly help with computational biology research. Concretely, this talk covers 3 exemplar use cases: (1) Discovering safe drug-drug combinations via multi-relational link prediction on heterogenous knowledge graphs; (2) Classify patient outcomes and diseases via learning subgraph embeddings; and (3) Learning effective disease treatments through few-shot learning for graphs.

๐Ÿ“ฝ Watch

๐Ÿ“ฒChannel: @ComplexNetworkAnalysis

#video #course #Graph #GNN #Machine_Learning #computational_biology
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๐ŸŽ“Study of Tensor Network Applications in Complex Networks

๐Ÿ“˜Integrated master's thesis in engineering physics

๐Ÿ—“Publish year: 2022

๐Ÿ“ŽStudy Thesis

๐Ÿ“ฑChannel: @ComplexNetworkAnalysis

#Thesis #Tensor_Networks #Application
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๐Ÿ“ƒData-centric Graph Learning: A Survey

๐Ÿ“˜ Journal: JOURNAL OF LATEX CLASS FILES
๐Ÿ—“ Publish year: 2021

๐Ÿง‘โ€๐Ÿ’ปAuthors: Yuxin Guo, Deyu Bo, Cheng Yang, Zhiyuan Lu, Zhongjian Zhang, Jixi Liu, Yufei Peng, Chuan Shi
๐ŸขUniversities: Beijing University of Posts and Telecommunications

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๐Ÿ“ฒChannel: @ComplexNetworkAnalysis
#paper #crime #Graph_Learning #Survey
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๐Ÿ“ƒComprehensive evaluation of deep and graph learning on drugโ€“drug interactions prediction

๐Ÿ“˜ Journal: Briefings in Bioinformatics(I.F=13.994)
๐Ÿ—“ Publish year: 2023

๐Ÿง‘โ€๐Ÿ’ปAuthors: Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S Yu, Xiangxiang Zeng
๐ŸขUniversities: Xiangtan University, Huazhong Agricultural University, Hunan University,

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๐Ÿ“ฒChannel: @ComplexNetworkAnalysis
#paper #drug_drug_interactions #Graph_Learning #deep_learning #prediction
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๐Ÿ“ƒ A review of Graph Neural Networks for Electroencephalography data analysis

๐Ÿ“˜
Journal: Neurocomputing (I.F=6)
๐Ÿ—“ Publish year: 2023

๐Ÿง‘โ€๐Ÿ’ปAuthors: Manuel Graรฑa, Igone Morais-Quilez
๐ŸขUniversity: University of the Basque Country (UPV/EHU), San Sebastian, Spain

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๐Ÿ“ฑChannel: @ComplexNetworkAnalysis
#paper #GNN #Electroencephalography #review
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๐Ÿ“•Handbook on Biological networks

โœจNetworks at the Cellular Level
-The Structural Network Properties of Biological Systems (M Brilli & P Liรณ)
-Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.)
-Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert)
-Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A Dรญaz-Guilera & R รlvarez-Buylla)
-Geometry and Topology of Folding Landscapes (L Bongini & L Casetti)
-Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.)
-Metabolic Networks (M C Palumbo et al.)
โœจBrain Networks:
-The Human
Brain Network (O Sporns)
-Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni)
-An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.)
-Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.)
-Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme)
โœจNetworks at the Individual and Population Levels:
-Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.)
-Evolutionary Models for Simple Biosystems (F Bagnoli)
-Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.)
-From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.)
-Interplay of Network State and Topology in Epidemic Dynamics (T Gross)

๐ŸŒ Read online

๐Ÿ“ฒChannel: @ComplexNetworkAnalysis

#Handbook #Biological
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๐Ÿ“ƒMultilayer Clustered Graph Learning

๐Ÿ—“ Publish year: 2020

๐Ÿง‘โ€๐Ÿ’ปAuthors: Mireille El Gheche, Pascal Frossard
๐ŸขUniversities: Ecole Polytechnique Fedยด erale de Lausanne (EPFL)

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#paper #Graph_Learning #Multilayer_graph
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๐Ÿ“ƒSimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning

๐Ÿ—“ Publish year: 2023

๐Ÿง‘โ€๐Ÿ’ปAuthors: Keyu Duan, Qian Liu,Tat-Seng Chua, Shuicheng Yan, Wei Tsang Ooi, Qizhe Xie, Junxian He
๐ŸขUniversities: ENational University of Singapore, The Hong Kong University of Science and Technology

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๐Ÿ’ป Code

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#paper #Graph_Learning #Textual
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๐Ÿ“ƒ A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges

๐Ÿ—“ Publish year: 2024

๐Ÿง‘โ€๐Ÿ’ปAuthors: Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang

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๐Ÿ“ฑChannel: @ComplexNetworkAnalysis
#paper #GNN #Imbalance #Noise #Privacy #OOD_Challenges #Survey
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๐Ÿ“ƒGraph Condensation: A Survey

๐Ÿ—“ Publish year: 2023

๐Ÿง‘โ€๐Ÿ’ปAuthors: Xinyi Gao, Junliang Yu, Wei Jiang, Tong Chen, Wentao Zhang, Hongzhi Yin
๐ŸขUniversities: The University of Queensland, Peking University

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๐Ÿ“ฒChannel: @ComplexNetworkAnalysis
#paper #Graph_Condensation #Survey
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๐Ÿ“ƒA Survey on Knowledge Editing of Neural Networks

๐Ÿ—“ Publish year: 2023

๐Ÿง‘โ€๐Ÿ’ปAuthors: Vittorio Mazzia, Alessandro Pedrani, Andrea Caciolai, Kay Rottmann, Davide Bernardi
๐ŸขUniversities: Amazon

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๐Ÿ“ฒChannel: @ComplexNetworkAnalysis
#paper #Survey #Knowledge #Neural_Networks
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Forwarded from Bioinformatics
๐Ÿ“‘ Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine

๐Ÿ“—Journal: Briefings in Bioinformatics (I.F.= 9.5)
๐Ÿ—“ Publish year: 2024

๐Ÿง‘โ€๐Ÿ’ปAuthors: Peng Zhang, Dingfan Zhang, Wuai Zhou, ...
๐ŸขUniversity: Tsinghua University, China

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๐Ÿ“ฒChannel: @Bioinformatics
#review #pharmacology #network #ai #medicine
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๐Ÿ“ƒ Explainability in Graph Neural Networks: A Taxonomic Survey

๐Ÿ“˜
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
๐Ÿ—“ Publish year: 2022

๐Ÿง‘โ€๐Ÿ’ปAuthors: Hao Yuan, Haiyang Yu, Shurui Gui, and Shuiwang Ji
๐ŸขUniversity: Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

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#paper #Explainability #GNN #Taxonomic #Survey
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2024_Recent_advances_in_manufacturing_and_processing_technologies.pdf
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๐Ÿ“ƒ Recent advances in manufacturing and processing technologies through graph theoretical approach: A survey

๐Ÿ—“ Publish year: 2023
๐Ÿ“˜ Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence

๐Ÿง‘โ€๐Ÿ’ปAuthors: Parthiban Angamuthu;
Ram Dayal; Samdanielthompson Gabriel; Sathish Kumar Krishnamoorthy; Malaya Ranjan Kar

๐ŸขUniversities: Lovely Professional University, Madras Christian College,

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#paper #Survey #manufacturing #processing #technologies
๐Ÿ“ƒ Knowledge Graphs and their Applications in Civil Security

๐Ÿ—“ Publish year: 2020

๐Ÿง‘โ€๐Ÿ’ปAuthors: Simon Ott, Daria Liakhovets, Mina Schรผtz, Medina Andresel, Mihai Bartha, Sven Schlarb, Alexander Schindler
๐ŸขUniversity: Austrian Institute of Technology GmbH
Giefinggasse 4, 1210 Vienna, Austria

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#paper #Knowledge_Graph #Application #Civil_Security
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๐Ÿ“ƒKnowledge Graph Embedding: An Overview

๐Ÿ—“ Publish year: 2024
๐Ÿ“˜ Journal: APSIPA Transactions on Signal and Information Processing (I.F=3.2)

๐Ÿง‘โ€๐Ÿ’ปAuthors: Xiou Ge, Yun Cheng Wang, Bin Wang, C.-C. Jay Kuo
๐ŸขUniversities: University of Southern California, Institute for Infocomm Research (I2R)

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๐Ÿ“ฒChannel: @ComplexNetworkAnalysis
#paper #Overview #Knowledge_Graph
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๐Ÿ“‘ A Survey of Analytical Methods for Biological Network Analysis: Exploring the Molecular Terrain

๐Ÿ—“ Publish year: 2024
๐Ÿ“˜
Journal: Symmetry (I.F=2.7)

๐Ÿง‘โ€๐Ÿ’ปAuthors: Trong-The Nguyen, Thi-Kien Dao, Duc-Tinh Pham, Thi-Hoan Duong
๐ŸขUniversities: Fujian University of Technology, China - University of Information Technology and Hanoi University of Industry, Vietnam

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๐Ÿ”ฎChannel: @ComplexNetworkAnalysis
#review #biology
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