#Dynamic network csv cytoscape how to#

Instead, they focused on specific biological processes (e.g., pathogenesis of specific disease) or specific sources of data (e.g., cDNA libraries). (7-10)The first high-throughput data sets made no attempt to map the entire interactome. High-throughput methods for interaction detection became generally available around 18 years ago (reviewed in ref 2 *), resulting in an explosion of protein–protein interaction data and motivating a number of serious attempts to produce large and semicomprehensive maps of protein–protein interactions.

#Dynamic network csv cytoscape how to#

Using the molecular interaction database IntAct, the software platform Cytoscape, and its plugins BiNGO and clusterMaker, and taking as a starting point a list of proteins identified in a mass spectrometry-based proteomics experiment, we show how to build, visualize, and analyze a protein–protein interaction network.

In this tutorial, we aim to give an overview of the key aspects that any researcher needs to consider when working with molecular interaction data sets and we outline an example for interactome analysis. The inherently artificial nature of interaction detection methods and the incompleteness of currently available interaction maps call for a careful and well-informed utilization of this valuable data. Molecular interaction networks provide a framework to visualize cellular processes, but their complexity often makes their interpretation an overwhelming task. The advent of the “omics” era in biology research has brought new challenges and requires the development of novel strategies to answer previously intractable questions.