gyorilab/indra_db

A Database-based knowledge back-end built on and for INDRA. The INDRA Database is a service that can be set up by any user with their own content and knowledge access. Our implementation of the database is the back-end to many of our projects, providing a vast and detailed knowledge base derived from many resources.

INDRA DB

The INDRA (Integrated Network and Dynamical Reasoning Assembler) Database is a framework for creating, maintaining, and accessing a database of content, readings, and statements. This implementation is currently designed to work primarily with Amazon Web Services RDS running Postrgres 9+. Used as a backend to INDRA, the INDRA Database provides a systematic way of scaling the knowledge acquired from other databases, reading, and manual input, and puts that knowledge at your fingertips through a direct Python client and a REST api.

REST API

The INDRA DB is available via a web UI at: https://db.indra.bio

At the same URL, a REST service is also available which allows for programmatic usage as documented here: https://github.com/gyorilab/indra_db/blob/master/indra_db_service/README.md

A convenient way to query the INDRA DB is via INDRA's built-in client towards INDRA DB which is documented here: https://indra.readthedocs.io/en/latest/modules/sources/indra_db_rest/index.html.

Knowledge sources

The INDRA Database currently integrates and distills knowledge from several different sources, both biology-focused natural language processing systems and other pre-existing databases

Daily Readers

We have read all available content, and every day we run the following readers:

• REACH
• Sparser

we read all new content with the following readers:

• Eidos
• ISI
• MTI - used specifically to tag content with topic terms.

we read a limited subset of new content with the following readers:

• TRIPS

on the latest content drawn from:

• PubMed - ~19 million abstracts and ~29 million titles
• PubMed Central - ~2.7 million fulltext
• Elsevier - ~0.7 million fulltext (requires special access)

Other Readers

We also include more or less static content extracted from the following readers:

• RLIMS-P

Other Databases

We include the information from these pre-existing databases:

• Pathway Commons database
• BEL Large Corpus
• SIGNOR
• BioGRID
• TAS
• TRRUST
• PhosphoSitePlus
• Causal Biological Networks Database
• VirHostNet
• CTD
• Phospho.ELM
• DrugBank
• CONIB
• CRoG
• DGI

These databases are retrieved primarily using the tools in indra.sources. The statements extracted from all of these sources are stored and updated in the database.

Knowledge Assembly

The INDRA Database uses the powerful internal assembly tools available in INDRA but implemented for large-scale incremental assembly. The resulting corpus of cleaned and de-duplicated statements, each with fully maintained provenance, is the primary product of the database.

For more details on the internal assembly process of INDRA, see the INDRA documentation.

Access

The content in the database can be accessed by those that created it using the indra_db.client submodule. This repo also implements a REST API which can be used by those without direct acccess to the database. For access to our REST API, please contact the authors.

Installation

The INDRA database only works for Python 3.6+, though some parts are still compatible with 3.5.

First, install INDRA, then simply clone this repo, and make sure that it is visible in your PYTHONPATH.

Funding

The development of INDRA DB is funded under the DARPA Communicating with Computers program (ARO grant W911NF-15-1-0544).