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sorgerlab/bioagents

Name: bioagents

Owner: sorgerlab

Description: Biological reasoning agents

Created: 2015-11-07 19:04:43.0

Updated: 2016-10-29 13:53:11.0

Pushed: 2017-11-21 00:11:00.0

Homepage: null

Size: 4303

Language: Python

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README

Biological reasoning agents

A collection of agents for biological reasoning in a communication system. The following agents are currently available:

MRA (Mechanistic Reasoning Agent): The MRA uses INDRA to construct mechanistic models of biochemical systems from user input, publications and databases. It can also propose changes to model structure autonomously.
TRA (Temporal Reasoning Agent): The TRA executes dynamical models built by the MRA under variable experimental conditions and verifies whether the dynamics meets a given temporal pattern
DTDA (Disease, Target and Drug Agent): The DTDA's task is to search for targets known to be implicated in a disease and to look for drugs that are known to affect that target.

KQML messaging classes used by the agents are available at: https://github.com/bgyori/pykqml

Installing the bioagents

Note that currently the bioagents have limited usage on their own. They are meant to be launched in the context of a communication system.

The bioagents depend on the following non-default python packages: objectpath, rdflib, functools32, requests, lxml, pandas.

The MRA uses INDRA to assemble models based on a natural language description of mechanisms. Please follow the more detailed instructions on the INDRA page to install it and its dependencies:

pip install git+https://github.com/sorgerlab/indra.git

INDRA depends on PySB, which is best installed from Github:

pip install git+https://github.com/pysb/pysb.git

PySB depends on BioNetGen. Make sure that BioNetGen is unzipped into /usr/local/share/BioNetGen, such that BNG2.pl is located at /usr/local/share/BioNetGen/BNG2.pl. Alternatively, set BNGPATH to the folder in which BNG2.pl is.

This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.