INDRA documentation¶
INDRA (the Integrated Network and Dynamical Reasoning Assembler) assembles information about biochemical mechanisms into a common format that can be used to build several different kinds of explanatory models. Sources of mechanistic information include pathway databases, natural language descriptions of mechanisms by human curators, and findings extracted from the literature by text mining. Mechanistic information from multiple sources is de-duplicated, standardized and assembled into sets of mechanistic Statements with associated evidence. Sets of Statements can then be used to assemble both executable rule-based models (using PySB) and a variety of different types of network models.
License and funding¶
INDRA is made available under the 2-clause BSD license. Users are asked to acknowledge DARPA grant W911NF-14-1-0397, “Programmatic modelling for reasoning across complex mechanisms,” Peter Sorger and Dexter Pratt PIs.
Contents:
- Installation
- Getting started with INDRA
- INDRA modules reference
- INDRA Statements (
indra.statements
) - Processors for model input (
indra.sources
) - Database clients (
indra.databases
)- HGNC client (
indra.hgnc_client
) - Uniprot client (
indra.databases.uniprot_client
) - ChEBI client (
indra.databases.chebi_client
) - BioGRID client (
indra.databases.biogrid_client
) - Cell type context client (
indra.databases.context_client
) - Network relevance client (
indra.databases.relevance_client
) - NDEx client (
indra.databases.ndex_client
) - cBio portal client (
indra.databases.cbio_client
)
- HGNC client (
- Literature clients (
indra.literature
) - Preassembly (
indra.preassembler
) - Belief Engine (
indra.belief
) - Mechanism Linker (
indra.mechlinker
) - Assemblers of model output (
indra.assemblers
)- Executable PySB models (
indra.assemblers.pysb_assembler
) - Cytoscape networks (
indra.assemblers.cx_assembler
) - Natural language (
indra.assemblers.english_assembler
) - Node-edge graphs (
indra.assemblers.graph_assembler
) - SIF / Boolean networks (
indra.assemblers.sif_assembler
) - MITRE “index cards” (
indra.assemblers.index_card_assembler
) - SBGN output (
indra.assemblers.sbgn_assembler
)
- Executable PySB models (
- Explanation (
indra.explanation
) - Tools (
indra.tools
)- Run assembly components in a pipeline (
indra.tools.assemble_corpus
) - Build a network from a gene list (
indra.tools.gene_network
) - Build an executable model from a fragment of a large network (
indra.tools.executable_subnetwork
) - Build a model incrementally over time (
indra.tools.incremental_model
) - High-throughput reading tools (
indra.tools.reading
) - Scoring INDRA Statements manually (
indra.tools.stmt_scoring
) - Generate English language questions on linked mechanisms (
indra.tools.mechlinker_queries
)
- Run assembly components in a pipeline (
- INDRA Statements (
- Tutorials
- Using natural language to build models
- Large-Scale Machine Reading with Starcluster
- Large-Scale Machine Reading with Amazon Batch
- Assembling everything known about a particular gene
- Collect mechanisms from PathwayCommons and the BEL Large Corpus
- Collect a list of publications that discuss the gene of interest
- Get the full text or abstract corresponding to the publications
- Read the content of the publications
- Combine all statements and run pre-assembly
- Assemble the statements into a network model
- REST API