Understanding Disease mechanism of Action by Integrative network-based approach

Question

[Bioinformatist Newbie]

If somebody wants to look at all aspect of biological information about a system (epigenomic, transcriptomic and proteomic) will it be helpful in understanding the disease mechanism of action?

If yes, How?

How we can integrate all these omics approaches to let's say get a network which can help us in doing this?

I've spent a couple of days looking into it but I am unable to get some comprehensive information about it (perhaps due to lack of understanding the complex review articles). If someone can shed some light on it by describing this thing in detail or share some relevant article then it will be very helpful..

Answer 1

[Jean-Karim Heriche]

The field is mostly known for works on gene prioritization. You can find many tools and references here and here. One popular approach to the data integration problem is to consider each data set as a graph. Typically these graphs have genes as nodes. You have then different approaches to combine the data: you can consider it as a multi-graph (i.e. a graph with multiple edges between two nodes, example here) or get a summary graph by combining the edges (e.g. by weighted average, see GeneMANIA) or derive kernels on graph nodes and combine these (e.g. FUNL).