Metadata-Version: 2.1
Name: gilda
Version: 0.8.3
Summary: Grounding for biomedical entities with contextual disambiguation
Home-page: https://github.com/indralab/gilda
Author: Benjamin M. Gyori, Harvard Medical School
Author-email: benjamin_gyori@hms.harvard.edu
License: UNKNOWN
Description: # Gilda: Grounding Integrating Learned Disambiguation
        [![License](https://img.shields.io/badge/License-BSD%202--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause)
        [![Build](https://github.com/indralab/gilda/actions/workflows/tests.yml/badge.svg)](https://github.com/indralab/gilda/actions)
        [![Documentation](https://readthedocs.org/projects/gilda/badge/?version=latest)](https://gilda.readthedocs.io/en/latest/?badge=latest)
        [![PyPI version](https://badge.fury.io/py/gilda.svg)](https://badge.fury.io/py/gilda)
        
        Gilda is a Python package and REST service that grounds (i.e., finds
        appropriate identifiers in namespaces for) named entities in biomedical text.
        
        ## Installation
        Gilda is deployed as a web service at http://grounding.indra.bio/ (see
        Usage instructions below), however, it can also be used locally as a Python
        package.
        
        The recommended method to install Gilda is through PyPI as
        ```bash
        pip install gilda
        ```
        Note that Gilda uses a single large resource file for grounding, which is
        automatically downloaded into the `~/.data/gilda/<version>` folder during
        runtime (see [pystow](https://github.com/cthoyt/pystow#%EF%B8%8F-configuration) for options to
        configure the location of this folder).
        
        Given some additional dependencies, the grounding resource file can
        also be regenerated locally by running `python -m gilda.generate_terms`.
        
        ## Usage
        Gilda can either be used as a REST web service or used programmatically
        via its Python API. An introduction Jupyter notebook for using Gilda
        is available at
        https://github.com/indralab/gilda/blob/master/notebooks/gilda_introduction.ipynb
        
        ### Use as a Python package
        For using Gilda as a Python package, the documentation at
        http://gilda.readthedocs.org provides detailed descriptions of each module of
        Gilda and their usage. A basic usage example is as follows
        
        ```python
        import gilda
        scored_matches = gilda.ground('ER', context='Calcium is released from the ER.')
        ```
        
        ### Use as a web service
        The REST service accepts POST requests with a JSON header on the /ground
        endpoint.  There is a public REST service running on AWS but the service can
        also be run locally as
        
        ```bash
        python -m gilda.app
        ```
        which, by default, launches the server at `localhost:8001` (for local usage
        replace the URL in the examples below with this address).
        
        Below is an example request using `curl`:
        
        ```bash
        curl -X POST -H "Content-Type: application/json" -d '{"text": "kras"}' http://grounding.indra.bio/ground
        ```
        
        The same request using Python's request package would be as follows:
        
        ```python
        import requests
        requests.post('http://grounding.indra.bio/ground', json={'text': 'kras'})
        ```
        
        ## Run web service with Docker
        
        After cloning the repository locally, you can build and run a Docker image
        of Gilda using the following commands:
        
        ```shell
        $ docker build -t gilda:latest .
        $ docker run -d -p 8001:8001 gilda:latest
        ```
        
        Alternatively, you can use `docker-compose` to do both the initial build and
        run the container based on the `docker-compose.yml` configuration:
        
        ```shell
        $ docker-compose up
        ```
        
        ## Citation
        
        ```bibtex
        @article{gyori2021gilda,
          author = {Gyori, Benjamin M and Hoyt, Charles Tapley and Steppi, Albert},
          doi = {10.1101/2021.09.10.459803},
          journal = {bioRxiv},
          publisher = {Cold Spring Harbor Laboratory},
          title = {{Gilda: biomedical entity text normalization with machine-learned disambiguation as a service}},
          url = {https://www.biorxiv.org/content/10.1101/2021.09.10.459803v1},
          year = {2021}
        }
        ```
        
        ## Funding
        The development of Gilda was funded under the DARPA Communicating with Computers
        program (ARO grant W911NF-15-1-0544) and the DARPA Young Faculty Award
        (ARO grant W911NF-20-1-0255).
        
Keywords: nlp,biology
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: terms
Provides-Extra: benchmarks
