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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.

Suggestions?

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    $\begingroup$ What type of genetics? $\endgroup$ – canadianer Jun 16 '15 at 16:38
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    $\begingroup$ You should clarify what you really require in detail. Else this would count as duplicate of the abovementioned post. $\endgroup$ – WYSIWYG Jun 16 '15 at 19:05
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GENETICS: Analysis and Principles, 4th edition, Robert J. Booker

This book is used in my school's ( NYU Poly) undergraduate genetics class.

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MIT Open Course Ware has a course on genetics, which uses the following text:

"An Introduction to Genetic Analysis", Griffiths, Anthony J. F., Jeffrey H. Miller, David T. Suzuki, Richard C. Lewontin, and William M. Gelbart, 7th ed. New York: W. H. Freeman, 2000.

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