Anyone interested in working on Graph LSTMs with me?

I’m interested in implementing a special LSTM architecture called “Graph LSTM” described in this paper : “Cross-Sentence N-ary Relation Extraction with Graph LSTMs” by Peng et al. with particular focus on their application of finding ternary relationships in multi-sentence texts.

They apply it to biomedical articles and that is a very interesting area for me. The goal is to extract the relationship between a Drug, Gene and Variant (Mutation) and determine if the patient would respond to the drug or not. I would want to expand the relationship to a QUARTERNARY relation, also including the disease or condition of the patient…

Example: “It is possible to conceive that an increase in the clinical doses of gefitinib or switching to erlotinib , which is given at its maximal tolerated dose [ ] , may lead to beneficial clinical effects , possibly by increasing BIM expression , in patients with EGFR mutations who acquired L747S after exposure to gefitinib . The data presented here indicate that BIM is both a marker and an effector of TKI induced apoptosis in EGFR-mutant NSCLC cells . Furthermore , we identified a novel acquired EGFR secondary mutation , L747S , and showed that both the L747S and the common T790M in cis to an activating EGFR mutation ( either L858R or an exon 19 deletion ) cause resistance to EGFR TKI induced apoptosis and attenuate the up-regulation of BIM.”

That sentence contains the following quaternary relationship

DRUGS: [afatinib || erlotinib)
GENES: EGFR
MUTATIONS: [(L747S || T790M) && (L858R || exon 19 deletion)]
DISEASE: NSCLC (Non-Small-Cell Lung Carcinoma)
RELATIONSHIP: Resistant

There is a nice description of the Graph LSTM in the paper, but it is a little too complicated for my Biologist brain to comprehend and know how to implement this model architecture in FASTAI.

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(My intuition on this is that the idea of “Attention” is somewhat similar here, since rather than discovering a relationship between Sequence 1 and Sequence 2, there is a relationship between Sentence t-1 and sentence t (and Sentence t+1) in Sequence 1, but this may just be nothing…)

So, if anyone is interested in working on this with me, drop me a line!

Thon

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Hi,
What would be the advantages of using a Graph LSTM exactly. Just trying to understand it