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1. Today we will demonstrate how to interact with the MiMI database. This mechanism is a Discovery approach starting from a single protein of interest to explore other possible protein interactions

Bring up Cytoscape window, pre-loaded with TCF7L2

1.a.i. We will show how to use the Mimi Plug-in for Cytoscape to retrieve protein interactions, and to visually display them. We will highlight certain features of the Mimi Plug-in. Firstly input search parameters

Search parameters for single gene and file

1.a.ii. Secondly show the text panel for nodes

CTRL A to select all nodes. Open the text panel and select: Description, Gene, Other Gene Names, process, function, and Pathways

Show that columns can be switched and be sorted on

1.b.i. We will show the seamless integration between Cytoscape and the SAGA tool. SAGA is a subgraph approximate matching tool written by Yuanyuan Tian in the laboratory of Dr. Jignesh Patel.

Select ALL nodes (CTRL+ALT+A) Right Click and select SAGA. Show the scoring and matches between the submitted network and the KEGG Matching pathways

Blue lines are matching relationships, Red Lines are matching proteins

1.b.ii. Show how this links to the annotated KEGG Pathway

by clicking on the “Link to KEGG Picture” at the top of the match. Show how the matches to your submitted proteins align to this picture.

Tian Y, McEachin RC, Santos C, States DJ, Patel JM. SAGA: a subgraph matching tool for biological graphs. Bioinformatics. 2007; 23(2):232-9.

1.c. Edge information description

All nodes and edges should still be selected when you return to Cytoscape window. Click on the Edge Attribute tab at bottom and choose attributes: Genename, Provenance and Type. Show how to sort, and how to identify in the image which edge you’ve selected

1.d. We will show how the Mimi provenance is visible through the browser

Discuss MIMI Provenance here, and show NLP Only attributed relationships.

1.e. We will show you the integration of the parsed PubMed abstract literature data (bioNLP) , and how to connect out to pubmed for the abstract information if needed.

Returning to a single edge, we select PARP1 and TCF7L2 edge and right click to get BioNLP data. Discuss 3 different Abstracts and ability to link out. Mention MEAD summarization for large numbers of sentences – don’t demo this