Great work. At Lawrence Berkeley National Lab in the biosciences (formerly life sciences) division, headed by Mina Bissell[1], one of the leading researchers of breast cancer, we developed NLP-based vector space modeling (embedding) in 2002 to augment genomic research in breast cancer, the extracellular matrix and aging. That was about 2 years after the first human genome was sequenced. The Lab patented[2] some of our methods and it helped pave the way for approaches like word2vec and a few others. There's a lot of great work yet to be in this area and we continue to make slow and steady progress defined by generating new insights, hypotheses and sometimes discoveries using approaches in NLP/NLU. We've recently been applying vector space modeling in NLU to LET radiation research (DNA damage repair) associated to space biosciences[3] which is exciting for extending and protecting human lifespan for space travel. Interdisciplinary aspects are key.
[1] https://www2.lbl.gov/LBL-Programs/lifesciences/BissellLab/ma...
[2] http://www.google.com/patents/US7987191
[3] https://www.nasa.gov/ames/research/space-biosciences/for-res...