Code to accompany the paper: ”ProteinNetworkSight efficiently transforms co-expressed protein lists into interactive networks and offers suggestions for their modifications”
This file contains the Flask routes and API endpoints for the application.
This folder contains various modules and functions used by the Flask application.
This file contains the cal_string_id
function used in the /api/validate
route to validate a name and return a matching ID.
This file contains the make_graph_data
function used in the /api/graphs
route to generate nodes and links for creating a graph.
This file contains the get_organism_list
function used in the /api/organism
route to retrieve a list of available organisms.
This file contains the register_user
function used in the /api/user
route to create a new user table.
This file contains the cal_string_suggestions
function used in the /api/names
route to provide suggestions for matching names.
/api/
(GET): Returns a welcome message./api/organism
(GET): Returns a list of available organisms./api/names
(POST): Given a list of organism names and an organism, returns a list of matching names with suggestions./api/validate
(POST): Given a name and an organism, returns a matching ID./api/user
(POST): Creates a new user table with provided proteins, IDs, and string names./api/graphs
(POST): Given a user ID, values map, and thresholds, returns nodes and links for creating a graph.
This is not a full installation for this project some parts are left out. (like a postgres installation with the STRING DB)
- Clone the repository.
- Install the required dependencies (e.g., Flask, Flask-CORS).
- Navigate to the project directory.
- Run the Flask application with
python routes.py
. - The server will start running on
http://0.0.0.0:3000
.
The application likely uses some data sources or databases to retrieve information about organisms, proteins, and their interactions. The specific data sources are not included in the provided code.