Network Analysis Resources & Updates - Статистика та аналітика Telegram каналу @complexnetworkanalysis

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🎓Analysis of the Structural Properties and Scalability of Complex Networks 📘A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA 🗓Publish year: 2018 📎Study dissertation 📱Channel: @ComplexNetworkAnalysis #dissertation #scalability

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🎓Analysis of the Structural Properties and Scalability of Complex Networks 📘A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA 🗓Publish year: 2018 📎Study paper 📱Channel: @ComplexNetworkAnalysis #Dissertation #Scalability

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📄Applications of network analysis to routinely collected health care data: a systematic review 📘Journal: Journal of the American Medical Informatics Association (I.F=7.942) 🗓Publish year: 2018 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Applications #health_care #review

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🎞 Methods in building and analysing biological networks 💥Free recorded webinar series 📽 Watch 📱Channel: @ComplexNetworkAnalysis #video #webinar #biological_networks

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📄New perspectives on analysing data from biological collections based on social network analytics 📘Journal: SCIENTIFIC REPORTS (I.F=4.996) 🗓Publish year: 2020 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #biological

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🎞 Machine Learning with Graphs: Applications of Graph ML 💥Free recorded course by Jure Leskovec, Computer Science, PhD 💥Graph machine learning can be applied in many scenarios, including the tasks of node classification, link prediction, graph classification, etc. Machine Learning at different levels of graphs usually demonstrate powerful capability in many specific tasks in different fields, ranging from protein folding, drug discovery, to recommender system, traffic prediction, among various other tasks. 📽 Watch 📜 Slides 💻Codes: part1 part2 📲Channel: @ComplexNetworkAnalysis #video #course #Graph #Machine_Learning #code #python

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📄Complex network approaches to nonlinear time series analysis 📘Journal: Physics Reports (I.F=25.6) 🗓Publish year: 2019 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #time_series

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🎞 clustering and motifs 💥Free recorded course 📽 Watch 📲Channel: @ComplexNetworkAnalysis #video #course #clustering #motif

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📄Complex Network: Facebook friends list 💥Technical paper 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper

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📄Cliques, Clusters and Components 💥Technical paper 💥Social Network Analysis for Startups by Maksim Tsvetovat, Alexander 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper #Clustering #Graph #Code #Python

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📄INTRODUCTION TO COMPLEX NETWORK ANALYSIS 💥Technical paper 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper

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📄Network-based machine learning and graph theory algorithms for precision oncology 📘Journal: npj Precision Oncology(I.F=10.092) 🗓Publish year: 2017 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #machine_Learning #graph

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🎞 Consul and Complex Networks 💥Free recorded course by James Phillips, Consul Lead at HashiCorp 💥A systematic overview of Consul's different network models, how they work, what kind of use cases they serve, and how prepared queries can help provide glue to keep service discovery simple across all. 📽 Watch 📲Channel: @ComplexNetworkAnalysis #video #course #Consul

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📄Social Network Analysis and Spectral Clustering in Graphs and Networks 💥Technical paper 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper #Spectral_Clustering #Graph #Code #Python

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📄Social Network Analysis and Spectral Clustering in Graphs and Networks 💥Technical paper 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper #Spectral_Clustering #Graph #Code #Python

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🎞 Network Analysis in Systems Biology 💥Free recorded course by Avi Ma’ayan, PhD 💥An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools. The course is mostly appropriate for beginning graduate students and advanced undergraduates majoring in fields such as biology, math, physics, chemistry, computer science, biomedical and electrical engineering. The course should be useful for researchers who encounter large datasets in their own research. The course presents software tools developed by the Ma’ayan Laboratory 📽 Watch 📲Channel: @ComplexNetworkAnalysis #video #course #Biology

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📄A survey of game theory as applied to social networks 📘Journal: T singhua Science and Technology (I.F=3.515) 🗓Publish year: 2020 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #game_theory #survey

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📄A survey of game theory as applied to social networks 📘Journal: T singhua Science and Technology (I.F=3.515) 🗓Publish year: 2020 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #game_theory #survey

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📄Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale 📘Journal: PLOS ONE(I.F=3.752) 🗓Publish year: 2016 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #Clustering

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📄Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale 📘Journal: PLOS ONE(I.F=3.752) 🗓Publish year: 2016 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #Clustering