activity
20192022
most citedKnowledge Graph Embedding for Ecotoxicological Effect Prediction

19 citations · 33 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2022

Understanding Adverse Biological Effect Predictions Using Knowledge Graphs

Erik Bryhn Myklebust, Ernesto Jimenez-Ruiz, Jiaoyan Chen +2

Extrapolation of adverse biological (toxic) effects of chemicals is an important contribution to expand available hazard data in (eco)toxicology without the use of animals in labor…

cs.AI2021★ 2 cited

Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

Erik B. Myklebust, Ernesto Jiménez-Ruiz, Jiaoyan Chen +2

We have created a knowledge graph based on major data sources used in ecotoxicological risk assessment. We have applied this knowledge graph to an important task in risk assessment…

cs.AI2020★ 12 cited

Correcting Knowledge Base Assertions

Jiaoyan Chen, Xi Chen, Ian Horrocks +2

The usefulness and usability of knowledge bases (KBs) is often limited by quality issues. One common issue is the presence of erroneous assertions, often caused by lexical or seman…

cs.AI2019

TERA: the Toxicological Effect and Risk Assessment Knowledge Graph

Erik Bryhn Myklebust, Ernesto Jimenez-Ruiz, Jiaoyan Chen +2

Ecological risk assessment requires large amounts of chemical effect data from laboratory experiments. Due to experimental effort and animal welfare concerns it is desired to extra…

cs.AI2019★ 19 cited

Knowledge Graph Embedding for Ecotoxicological Effect Prediction

Erik Bryhn Myklebust, Ernesto Jimenez-Ruiz, Jiaoyan Chen +2

Exploring the effects a chemical compound has on a species takes a considerable experimental effort. Appropriate methods for estimating and suggesting new effects can dramatically…