PPT-Graph clustering to detect network modules

Author : tatyana-admore | Published Date : 2017-12-23

Sushmita Roy sroybiostatwiscedu Computational Network Biology Biostatistics amp Medical Informatics 826 Computer Sciences 838 httpscompnetbiocoursediscoverywiscedu

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Graph clustering to detect network modul..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Graph clustering to detect network modules: Transcript

Sushmita Roy sroybiostatwiscedu Computational Network Biology Biostatistics amp Medical Informatics 826 Computer Sciences 838 httpscompnetbiocoursediscoverywiscedu Nov 1 st 2016 Some material is adapted from lectures from Introduction to Bioinformatics. Why graph clustering is useful?. Distance matrices are graphs .  as useful as any other clustering. Identification of communities in social networks. Webpage clustering for better data management of web data. Adapted from Chapter 3. Of. Lei Tang and . Huan. Liu’s . Book. Slides prepared by . Qiang. Yang, . UST, . HongKong. 1. Chapter 3, Community Detection and Mining in Social Media. Lei Tang and Huan Liu, Morgan & Claypool, September, 2010. . Why graph clustering is useful?. Distance matrices are graphs .  as useful as any other clustering. Identification of communities in social networks. Webpage clustering for better data management of web data. Wei Wang. Department of Computer Science. Scalable Analytics Institute. UCLA. weiwang@cs.ucla.edu. Graphs/Networks. FFSM (ICDM03), SPIN (KDD04),. GDIndex. (ICDE07). MotifMining. (PSB04, RECOMB04, ProteinScience06, SSDBM07, BIBM08). and Physical Interaction . Datasets. Manikandan Narayanan, Adrian Vetta, Eric E. Schadt, Jun Zhu. PLoS Computational Biology 2010. Presented by: Tal Saiag. Seminar in Algorithmic Challenges in Analyzing Big Data* in Biology and . April 22, 2010. Last Time. GMM Model Adaptation. MAP (Maximum A Posteriori). MLLR (Maximum Likelihood Linear Regression). UMB-. MAP. for speaker recognition. Today. Graph Based Clustering. Minimum Cut. . social . and neural network data. Darren A. Narayan. Rochester Institute of Technology. Joint work with Roger Vargas, Williams College, Bradford Mahon and Frank Garcea, Rochester Center for Brain Imaging, University of Rochester. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. Computer Sciences 838. https://compnetbiocourse.discovery.wisc.edu. Nov 3. rd. 2016. RECAP. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. Computer Sciences 838. https://compnetbiocourse.discovery.wisc.edu. Nov 3. rd. , Nov 10. Why graph clustering is useful?. Distance matrices are graphs .  as useful as any other clustering. Identification of communities in social networks. Webpage clustering for better data management of web data. One of these things is not like the other…. spectral clustering (a la Ng-Jordan-Weiss). data. similarity graph. edges have weights . w. (. i. ,. j. ). e.g.. the . Laplacian. diagonal matrix . D. Normalized . Cluster Analysis. Outline. Introduction to Cluster Analysis. Types of Graph Cluster Analysis. Algorithms for Graph Clustering. k-Spanning Tree. Shared Nearest Neighbor. Betweenness Centrality Based. Highly Connected Components. Distance matrices are graphs .  as useful as any other clustering. Identification of communities in social networks. Webpage clustering for better data management of web data. Outline. Min s-t cut problem. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. https://compnetbiocourse.discovery.wisc.edu. Nov 1. st. 2018. Goals for today. Finding modules on graphs/Community structure on graphs/Graph clustering.

Download Document

Here is the link to download the presentation.
"Graph clustering to detect network modules"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.