Graph Analysis with Python

12:30 PM - 03:30 PM on August 16, 2014, Room 701

Adrian Heilbut

Audience level:
intermediate
Category:
Data Analysis

Description

This tutorial will provide a fast-paced, practical overview of analyzing network graph data using python, drawing on one case study from computational biology (protein and genetic interaction networks) and one from finance (correlation networks). We will compare and contrast the major libraries available for analyzing graphs with python (igraph, networkx, and graph-tool) as well as tools for graph visualization. Each section will consist of a 35 min talk/lecture, followed by a 25min guided laboratory exercise (presented as IPython notebooks) to demonstrate and apply the concepts.

Abstract

This tutorial will provide a fast-paced, practical overview of analyzing network graph data using python, drawing on one case study from computational biology (protein and genetic interaction networks) and one from finance (correlation networks). We will compare and contrast the major libraries available for analyzing graphs with python (igraph, networkx, and graph-tool) as well as tools for graph visualization. Each section will consist of a 35 min talk/lecture, followed by a 25min guided laboratory exercise (presented as IPython notebooks) to demonstrate and apply the concepts.