🎓Network analysis of a complex disease: the gut microbiota
in the infammatory bowel disease case
📘PhD's thesis from IMT School for Advanced Studies, Lucca, Italy
🗓Publish year: 2022
📎Study thesis
📲Channel: @ComplexNetworkAnalysis
#thesis
in the infammatory bowel disease case
📘PhD's thesis from IMT School for Advanced Studies, Lucca, Italy
🗓Publish year: 2022
📎Study thesis
📲Channel: @ComplexNetworkAnalysis
#thesis
🎞 Community detection in graphs (Alex Levin, PyData TLV - Oct 21)
💥Free recorded lecture
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Community_Detection
💥Free recorded lecture
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Community_Detection
YouTube
Community detection in graphs (Alex Levin, PyData TLV - Oct 21)
Community detection is a key tool in order to understand the structure of the graph. In this talk we will go over 2 popular algorithms (Louvain & BigCLAM), we will learn their theory and also see code examples..
📄A network analysis of research on African agricultural development
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #agricultural
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #agricultural
🎞Modularity Explained: A Metric for Community Detection in Graphs
💥Free recorded lecture
📽 Watch
📄 slides
📲Channel: @ComplexNetworkAnalysis
#video #Community_Detection
💥Free recorded lecture
📽 Watch
📄 slides
📲Channel: @ComplexNetworkAnalysis
#video #Community_Detection
YouTube
Modularity Explained: A Metric for Community Detection in Graphs
You can find the slides here: https://docs.google.com/presentation/d/1FiIPhd64LzqSeZ1axb7MKBTjkjMsF5bjqljIKrx8k18/edit?usp=sharing
📄Social network extraction based on Web: A Review about Supervised Methods
📘journal: Journal of Physics: Conference Series
🗓Publish year: 2021
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #review
📘journal: Journal of Physics: Conference Series
🗓Publish year: 2021
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #review
👍1
2017_A_Survey_of_Online_Social_Networks_Challenges_and_Opportunities.pdf
269 KB
📄A Survey of Online Social Networks: Challenges and Opportunities
📘Conference: 2017 IEEE International Conference on Information Reuse and Integration (IRI)
🗓Publish year: 2017
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #survey
📘Conference: 2017 IEEE International Conference on Information Reuse and Integration (IRI)
🗓Publish year: 2017
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #survey
📄Quantitative analysis of trade networks: data and robustness
📘Journal: Applied Network Science (I.F=2.65)
🗓Publish year: 2021
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
📘Journal: Applied Network Science (I.F=2.65)
🗓Publish year: 2021
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper
📄Knowledge Graph Mining: A Survey of Methods, Approaches, and Applications
🗓Publish year: 2020
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #survey #application
🗓Publish year: 2020
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #survey #application
📄Complex Network Approach to International Trade of Fossil Fuel
📘Journal: world academy of science
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Trade
📘Journal: world academy of science
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #Trade
👍1
2019_Community Detection in Social Networks.pdf
740.2 KB
📄Community Detection in Social Networks: Literature Review
📘Journal: Journal of Information & Knowledge Management
🗓Publish year: 2019
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #review
📘Journal: Journal of Information & Knowledge Management
🗓Publish year: 2019
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #review
🎞 Network models
💥Free recorded Lecture by Prof. Leonid Zhukov, Ilya Makarov.
💥Barabasi-Albert model. Preferential attachement. Time evolition of node degrees. Node degree distribution. Average path length and clustering coefficient. Small world model. Watts-Strogats model. Transition from ragular to random. Clustering coefficient and ave path lenght.
📽 Watch
📑 Lecture
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture by Prof. Leonid Zhukov, Ilya Makarov.
💥Barabasi-Albert model. Preferential attachement. Time evolition of node degrees. Node degree distribution. Average path length and clustering coefficient. Small world model. Watts-Strogats model. Transition from ragular to random. Clustering coefficient and ave path lenght.
📽 Watch
📑 Lecture
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Lecture 4. Network models.
Network Science 2021 @ HSE
http://www.leonidzhukov.net/hse/2021/networks/
http://www.leonidzhukov.net/hse/2021/networks/
👍1
👨🎓Research Fellow / Postdoc positions in Complex Networks and Brain Dynamics
(Institute of Computer Science, Czech Academy of Sciences)
💥They looking for new team members to join the Complex Networks and Brain Dynamics group to work on its interdisciplinary projects. The group is part of the Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences.
ℹ️ How to apply
📲Channel: @ComplexNetworkAnalysis
#apply #postdoc
(Institute of Computer Science, Czech Academy of Sciences)
💥They looking for new team members to join the Complex Networks and Brain Dynamics group to work on its interdisciplinary projects. The group is part of the Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences.
ℹ️ How to apply
📲Channel: @ComplexNetworkAnalysis
#apply #postdoc
👍1
🎤Next In Marketing S2 E3: Aaron Braxton, VP, Head of Business Intelligence, Complex Networks
💥Free recorded interview by Aaron Braxton, Vice President, Head of Business Intelligence at Complex Networks.
💥They talks about how even as his company is eyeing industry-wide attempts at replacing the cookie, such as the Trade Desk’s Unified ID initiative, publishers need to start taking audience intelligence into their own hands.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #interview
💥Free recorded interview by Aaron Braxton, Vice President, Head of Business Intelligence at Complex Networks.
💥They talks about how even as his company is eyeing industry-wide attempts at replacing the cookie, such as the Trade Desk’s Unified ID initiative, publishers need to start taking audience intelligence into their own hands.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #interview
👍1
2018-The evolution of oil trade A complex network approach.pdf
868.7 KB
📄The evolution of oil trade: A complex network approach
📘Published online by Cambridge University Press
🗓Publish year: 2018
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #trade
📘Published online by Cambridge University Press
🗓Publish year: 2018
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #trade
📄Centrality Measures in Complex Networks: A Survey
🗓Publish year: 2020
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #survey #centrality
🗓Publish year: 2020
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #survey #centrality
🎞 Statistical analysis of networks
💥Free recorded Lecture by Prof. Gesine Reinert in University of Oxford.
💥Networks have become increasingly popular as representations of complex data. How can we make sense of such data? The first class will cover some network summaries and some parametric models for networks, while the second class concerns statistical inference using these network summaries as well as parametric models. We shall also cover some nonparametric ideas.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture by Prof. Gesine Reinert in University of Oxford.
💥Networks have become increasingly popular as representations of complex data. How can we make sense of such data? The first class will cover some network summaries and some parametric models for networks, while the second class concerns statistical inference using these network summaries as well as parametric models. We shall also cover some nonparametric ideas.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Statistical analysis of networks - Professor Gesine Reinert, University of Oxford
Networks have become increasingly popular as representations of complex data. How can we make sense of such data? The first class will cover some network summaries and some parametric models for networks, while the second class concerns statistical inference…
📄Effect of network topology and node centrality on trading
📘Journal: scientific reports (I.F=4.379)
🗓Publish year: 2019
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #trade #centrality
📘Journal: scientific reports (I.F=4.379)
🗓Publish year: 2019
📎Study paper
📲Channel: @ComplexNetworkAnalysis
#paper #trade #centrality
👍1
🎞 Network-Based Modeling of Complex Systems
💥Free recorded Lecture by Dr. Fatena El-Masri from QuantCon 2018
💥This talk, titled Network-based Modeling of Complex Systems, with Applications to Cascading and Contagion Events in Networks, looks at how network-based modeling can be used to analyze cascading and contagious events in financial networks. Dr. El-Masri’s research started with the simulation of 63 million records to determine the network and dynamic connectivity between different banks. This connectivity is determined by transforming the adjacency matrix for the data using Python. The agent-based model is then applied using dynamic modeling and validated using real data. The results are then implemented using network-based modeling for complex financial institutions to discover the cascading and contagious event behavior in the networks.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture by Dr. Fatena El-Masri from QuantCon 2018
💥This talk, titled Network-based Modeling of Complex Systems, with Applications to Cascading and Contagion Events in Networks, looks at how network-based modeling can be used to analyze cascading and contagious events in financial networks. Dr. El-Masri’s research started with the simulation of 63 million records to determine the network and dynamic connectivity between different banks. This connectivity is determined by transforming the adjacency matrix for the data using Python. The agent-based model is then applied using dynamic modeling and validated using real data. The results are then implemented using network-based modeling for complex financial institutions to discover the cascading and contagious event behavior in the networks.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Network-Based Modeling of Complex Systems by Dr. Fatena El-Masri from QuantCon 2018
This talk, titled Network-based Modeling of Complex Systems, with Applications to Cascading and Contagion Events in Networks, looks at how network-based modeling can be used to analyze cascading and contagious events in financial networks. Dr. El-Masri’s…
Forwarded from Bioinformatics
💻 Deep Learning for Biological network analysis
https://academic.oup.com/bib/article/22/2/1515/5964185
📲Channel: @Bioinformatics
https://academic.oup.com/bib/article/22/2/1515/5964185
📲Channel: @Bioinformatics
👍2
👨🎓Postdoctoral/Research Fellow position in complex network analysis: Critical events detection
(Institute of Computer Science, Czech Academy of Sciences)
💥Postdoc or research fellow position is available to join the Complex Networks and Brain Dynamics group for the project: “Modelling and analysis of complex systems for safety of critical infrastructures“ as part of the National Center of Competence – Cybernetics and Artificial Intelligence funded by the Technology Agency of the Czech Republic, and related projects.
ℹ️ How to apply
📲Channel: @ComplexNetworkAnalysis
#apply #postdoc
(Institute of Computer Science, Czech Academy of Sciences)
💥Postdoc or research fellow position is available to join the Complex Networks and Brain Dynamics group for the project: “Modelling and analysis of complex systems for safety of critical infrastructures“ as part of the National Center of Competence – Cybernetics and Artificial Intelligence funded by the Technology Agency of the Czech Republic, and related projects.
ℹ️ How to apply
📲Channel: @ComplexNetworkAnalysis
#apply #postdoc