I am working in the field of neuroscience with a background in computer science. I try to find new ways of analyzing brain imaging data (mostly MRI, EEG, MEG, fMRI) with modern machine learning methods.
I would like to take a step up by adding genetics to the data arsenal. My work this far has found connections between some X and Y but not really shed insight to why things should be like that. I hope I could get a partial answer from biology.
To get started, I would need some good material to read. It does not matter if the content would be difficult in mathematical/statistical/technical aspects, but it should be approachable with limited knowledge in biology and/or chemistry and physics.