REST API (OpenAPI 3) interface of Datanator, a toolkit for discovering the data needed for modeling the biochemistry of cells.
A central goal of synthetic biology is to rationally design organisms. Similarly, a central goal of precision medicine is to tailor therapy to each patient based on their unique genome. Many engineering fields use computer-aided design (CAD) tools driven by mechanistic models to efficiently design complex systems such as planes. Analogously, more comprehensive and more predictive models of biological systems, such as whole-cell models, are needed to help bioengineers and physicians design biomachines and medical therapy.
One of the biggest bottlenecks to achieving such models is collecting and aggregating the large amount of data needed for model construction and verification. Due to advances in genomics and increased emphasis on data sharing, there is now extensive data about a wide range of biochemical entities and processes such as data about metabolite concentrations, RNA and protein abundances, and reaction rates. However, it remains difficult to utilize this information for modeling because the data scattered across numerous databases and publications; the data is described using different formats, identifiers, and units; and there are inadequate tools for finding relevant data for modeling a specific biological system in a specific environment.
The Datanator toolkit seeks to address these problems for biochemical modeling by providing investigators an integrated database of molecular data and tools for discovering relevant data for modeling projects and other meta analyses. Please see the About page for more information about the goals and features of Datanator.
The Datanator toolkit is composed of the following packages:
- Datanator: Tools for aggregating and integrating diverse data from diverse sources into a single dataset and searching these datasets
- Datanator-db: MongoDB server for Datanator-data
- Datanator-fulltext-db: ElasticSearch server for Datanator-data
- Datanator-query-python: Tools for querying Datanator-db and Datanator-fulltext-db
- Datanator-rest-api: This package, REST interface for Datanator-query-python
- Datanator-frontend: A web-based graphical user interface to Datanator-db.
This package provides a pythonic interface to programmatically access data stored in Datanator-db and Datanator-fulltext-db.
We recommend that users use the public, hosted version of Datanator-rest-api at https://api.datanator.info.
We recommend that developers install and run Datanator-rest-api locally. Below are instructions for installing and running Datanator-rest-api locally.
- Install
gitandpipenv
apt-get install git pipenv
- Clone this repository
git clone https://github.com/karrlab/datanator_rest_api
- Install this package
cd /path/to/datanator_rest_api
pipenv install -e .
- Spin up an independent python environment
pipenv shell
- Setup environment variables (credentials for accessing databases)
export USERNAME=XXXXXXX
export PASSWORD=XXXXXXX
export SERVER=XXXXXXX
export AUTHDB=XXXXXXX
export READ_PREFERENCE=XXXXXX
- Launch a server.
python datanator_rest_api/core.py
This repository is organized as follows:
datanator_rest_api/:routes/: API routesserver/: Compiler for definition filesspec/: Specifications for URL paths and data schemapaths/: Specifications for URLschemas/: Specifications for data schemaftx/: Specifications ftx-related data schemakegg/: Specifications KEGG-related data schemametabolites/: Specifications metabolite-related data schemaproteins/: Specifications protein-related data schemareactions/: Specifications reaction-related data schemaRNA/: Specifications RNA-related data schemataxon/: Specifications taxon-related data schema
util/: utility tools
tests/routes/: - test scripts inroutesdirectoryspec/: - test scripts inspecdirectoryutil/: - test scripts inutildirectory
nginx/: NGINX specification for production serverCODE_OF_CONDUCT: code of conductLICENSE: licensePipfile: package requirementsPipfile.lock: finalized package configurationREADME: overview of the applicationDockerfile: Specification for making a docker container
- Create a Git new branch
- Commit code to the new branch
- Push the branch to GitHub
- GitHub will automatically trigger CircleCI to run the unit test, integration tests, and other static analyses
- Use Coveralls to review the coverage of the tests
- As needed, add additional tests and fix any failing tests
- Once the new code passes the tests and has high coverage, create a pull request to merge the new branch into the master branch
- One of the main developers will review the pull request and request changes as necessary
- Once any necessary changes have been made, one of the main developers will approve the pull request
- GitHub will automatically trigger CircleCI to run the unit test, integration tests, and other static analyses for the master branch
- Once the CircleCI build succeeds, downstream dependencies will automatically be tested and built
We welcome contributions to Datanator via GitHub pull requests. Please contact the developers to coordinate potential contributions, and please see above for information about how to submit pull requests.
This package is released under the MIT license.
This package was developed by the Karr Lab at the Icahn School of Medicine at Mount Sinai in New York by the following individuals:
- Yosef Roth
- Yang Lian
- Jonathan Karr
- Saahith Pochiraju
- Bilal Shaikh
- Balazs Szigeti
Please submit an issue, or contact the Karr Lab with any questions or comments.
Datanator was developed with support from the Center for Reproducible Biomedical Modeling from the National Institute of Bioimaging and Bioengineering and the National Institute of General Medical Sciences of the National Institutes of Health and the National Science Foundation (awards P41EB023912 and R35GM119771).