Our latest paper in PLoS Computational Biology is out.
The project spanned over 2 years starting at the end of my first year of postdoctoral training until now. It has been a truly collaborative endeavor across institutions but also across sub-disciplines using text-mining, leveraging public genomic data across diseases and genotyping a human twin cohort subjected to experimental pain. A big thank to all my collaborators.
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002538
Briefly, we successfully demonstrated that ranking diseases by pain level using a literature co-citation approach and then extracting the gene whose expression change is associated with this ranking lead to interesting new pain gene candidate.
The beauty of the approach is that it can be apply to other concept than pain. For example, we show in the paper that we can significantly prioritize genes involve in inflammation in a similar fashion.
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