ltkb-no-vs-most
Classification model based on Liver toxicology knowledge base (https://www.fda.gov/science-research/liver-toxicity-knowledge-base-ltkb/drug-induced-liver-injury-rank-dilirank-dataset)
Modelling the classes "no DILI" or "most DILI"
For end-users
Type:
Trained model
API Type:
REST under OpenAPI2 specification
Categories:
API Definitions for OpenRiskNet applications and data, Predictive toxicology
Relevant OpenRiskNet case study:
ModelRX - Modelling for Prediction or Read Across
Provided by:
Uppsala Universitet
Login required:
No
Implementation status:
API documentation available (Swagger-OpenAPI v2), Containerised, Available as web service
Integration status:
Integrated application
Service integration operations completed:
Utilises the OpenRiskNet APIs to ensure that each service is accessible to our proposed interoperability layer.
Is annotated according to the semantic interoperability layer concept using defined ontologies.
Is containerised for easy deployment in virtual environments of OpenRiskNet instances.
Has documented scientific and technical background.
Is deployed into the OpenRiskNet reference environment.
Is listed in the OpenRiskNet discovery services.
Is listed in other central repositories like eInfraCentral, bio.tools and TeSS (ELIXIR).
Provides legal and ethical statements on how the service can be used.