IBRel

Framework for identifying biomedical relations

Citation:

Lamurias A, Clarke LA, Couto FM (2017) Extracting microRNA-gene relations from biomedical literature using distant supervision. PLOS ONE 12(3): e0171929. doi: 10.1371/journal.pone.0171929

Dependencies:

• Python 2.7 and Java 8
• Pre-processing:
  • Genia Sentence Splitter (requires ruby)
  • Python wrapper for Stanford CoreNLP
• Term recognition
  • Stanford NER 3.5.1
• Relation extraction
  • SVM-light-TK
  • Shallow Language Kernel
• requirements.txt - run pip install -r requirements.txt

Configuration

A Dockerfile is provided to help with the installation. Build and then run with the -i flag. After setting up the dependencies, you have to run python src/config/config.py to set up some values. You can use the CHEMDNER-patents sample data to check if the system is working correctly. Then run ./benchmarks/check_setup.sh to confirm if everything is set up correctly.

Usage

To run distant supervision multi-instance learning experiments, use src/trainevaluate.py and check mil.sh for an example.