generating biological network motifs
DESCRIPTION
Generating Biological Network Motifs. Sai Badey. Biological Networks. What are they? Biological vs Regular Networks* Terminology Motifs Vertices Edges. Overall Scope. Focus on efficiency Large networks Network generation. Project Aim. Random Network Generation - PowerPoint PPT PresentationTRANSCRIPT
Generating Biological Network Motifs
Sai Badey
Biological Networks What are they?
Biological vs Regular Networks*
Terminology Motifs Vertices Edges
Overall Scope Focus on efficiency
Large networks Network generation
Project Aim Random Network Generation
functions (keep # vertices & # edges constant) Swap the edges between outer-vertices Completely random generation Swap node degrees
Analysis & Comparisons Run z-testing on the generations for small to
extremely large graphs
Potential Results No difference
Compare efficiencies of generation methods Create a standard for network generation
Significant Difference Determine which is more accurate
Steps Amala Ghandi’s work
Looks through existing network Determines motif
Expansion Determine motif across several networks Compare different networks & performance Network Generation
Current Status Class Design
Network Class Jung Library Constructor, Copy constructor Network generation Analysis (z-test, motif searching, data collection)
Compare Networks Class Equals Comparison (highest degree node, motif comparison) Analysis (significant difference, etc)
To Do Function implementation
Combine with Amala Ghandi’s work
Learning Vectors Hash tables
Issues Lots of research
Sources Amala Ghandi’s paper
Sahand Khakabimamaghani, Iman Sharafuddin, Norbert Dichter, Ina Koch, Ali Masoudi-Nejad
QuateXelero: An Accelerated Exact Network Motif Detection Algorithm (Article)
Joseph Blitzstein and Persi Diaconis A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM
GRAPHS WITH PRESCRIBED DEGREES (Article)
Bjorn H. Junker & Falk Schreiber Analysis of Biological Networks (Book)
Questions?
Take node, change the order of the vertices