Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Last update: Nov 01, 2021

Overview

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020.

Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

A snapshot of TERA (the Toxicological Effect and Risk Assessment Knowledge Graph) is avalible as a Zenodo dataset:

To run the codes you must install KGE-Keras.

To reproduce results from paper run:

bash run.sh

This will take several days, depending on hardware avalible. 3-5 days on Nvidia GTX 1070ti. Set --MAX_TRIALS 0 to use default parameters.

Alternativly, unzip results.zip and run

python3 analyse_results.py

Related publications

Erik B. Myklebust, Ernesto Jimenez Ruiz, Jiaoyan Chen, Raoul Wolf, Knut Erik Tollefsen. Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings. Accepted for publication in the Semantic Web Journal, 2021. Paper REPOSITORY

Owner

Knowledge Graphs at the Norwegian Institute for Water Research

GitHub Repository

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Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Related tags

Overview

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020.

Related publications

Owner

Knowledge Graphs at the Norwegian Institute for Water Research

CoMoGAN: continuous model-guided image-to-image translation. CVPR 2021 oral.

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Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Related tags

Overview

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020.

Related publications

Owner

Knowledge Graphs at the Norwegian Institute for Water Research

CoMoGAN: continuous model-guided image-to-image translation. CVPR 2021 oral.

The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

Code for the paper "Location-aware Single Image Reflection Removal"

PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)

Deep Learning for Morphological Profiling

Survival analysis (SA) is a well-known statistical technique for the study of temporal events.

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

ISNAS-DIP: Image Specific Neural Architecture Search for Deep Image Prior [CVPR 2022]

This is the dataset for testing the robustness of various VO/VIO methods

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Code for the paper "Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness"

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The Body Part Regression (BPR) model translates the anatomy in a radiologic volume into a machine-interpretable form.

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