Get the code

git clone --recursive https://github.com/amalic/bern-docker.git

Prerequisites

• Lot's of disk space (~60 GB disk space)
• 32 GB Ram (see BERN project README)
• NVidia Docker
• Those files:
  • GNormPlus.zip (~4GB)
  • tmVarJava.zip ftp://ftp.ncbi.nlm.nih.gov/pub/lu/Suppl/tmVar2/tmVarJava.zip (~40GB)
  • CRF++-0.58.tar.gz (~4 MB)
  • biobert_ner_models.zip (~7GB)
  • data.zip (~750 MB)
  • resources.zip (~3 GB)

Download and extract all archives into externalData folder within this repository by running.

sh prerequisites.sh

You might want to get a coffee or learn a new programming language, depending on your internet connection.

Build

docker build -t bern-docker .

Run

docker run --name bern-docker --log-opt max-size=10m -d --rm --gpus all -p 80:8888 \
  -v $PWD/externalData/GNormPlusJava/Dictionary/:/app/GNormPlusJava/Dictionary/ \
  -v $PWD/externalData/tmVarJava/Database:/app/tmVarJava/Database \
  -v $PWD/externalData/biobert_ner_models/pretrainedBERT:/app/biobert_ner/pretrainedBERT/ \
  -v $PWD/externalData/biobert_ner_models/conf/:/app/biobert_ner/conf/ \
  -v $PWD/externalData/biobert_ner_models/tmp/:/app/biobert_ner/tmp/ \
  -v $PWD/externalData/biobert_ner_models/result/:/app/biobert_ner/result/ \
  -v $PWD/externalData/data/:/app/normalization/data/ \
  -v $PWD/externalData/resources/:/app/normalization/resources/ \
  bern-docker

Examples

Usage PMID(s) (HTTP GET)

• http://<YOUR_SERVER_ADDRESS>:<PORT>/?pmid=<a PMID or comma seperate PMIDs>&format=<json or pubtator>
• Example: http://localhost/?pmid=30429607&format=json&indent=true
• Example: http://localhost/?pmid=30429607&format=pubtator
• Example: http://localhost/?pmid=30429607,29446767&format=json&indent=true

Citation of original work

@article{kim2019neural,
  title={A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining},
  author={Kim, Donghyeon and Lee, Jinhyuk and So, Chan Ho and Jeon, Hwisang and Jeong, Minbyul and Choi, Yonghwa and Yoon, Wonjin and Sung, Mujeen and and Kang, Jaewoo},
  journal={IEEE Access},
  volume={7},
  pages={73729--73740},
  year={2019},
  publisher={IEEE}
}

@article{10.1093/bioinformatics/btz682,
    author = {Lee, Jinhyuk and Yoon, Wonjin and Kim, Sungdong and Kim, Donghyeon and Kim, Sunkyu and So, Chan Ho and Kang, Jaewoo},
    title = "{BioBERT: a pre-trained biomedical language representation model for biomedical text mining}",
    journal = {Bioinformatics},
    year = {2019},
    month = {09},
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btz682},
    url = {https://doi.org/10.1093/bioinformatics/btz682},
}