I wasn't sure which sub-forum would best address my questions, so I decided to go broad with this one.
My lab is investigating human gene expression and epigenetics. My specific project that I'm getting started on now is focusing on enhancers. One component of the project is looking at changes in the enrichment of histone modifications that are characteristic of enhancers (i.e. H3K27ac, H3K4me1/2, etc...) in response to a specific treatment. We have data already that the modifications do significantly change in response to our experimental treatments (we used high resolution mass spec for that). We also have a separate data set from an expression microarray that shows genes that have increased/decreased expression in response to our treatment. To pick up from here, I want to first hand-pick some candidate genes from the microarray data to run qPCRs and I'm most interested in genes that are known to have associated enhancers in the literature and hopefully some extensive ENCODE data from other cell lines.
So finally on to my specific question: what is the best way to go about mining all the literature and data out there to find the information that I want? Honestly, I'm a little overwhelmed by the massive amount of information collected as part of ENCODE. I've tried playing around with the tracks within the UCSC genome browser, but I have no idea what is the most efficient way to do this. I'd like to narrow down by defined enhancers and the enhancer histone PTMs and be able to specifically search the most significantly changed genes in my lab's microarray data (ChIP-seq data, I guess?).
I appreciate any guidance that all of you amazing scientists can provide!