CDR extraction

Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highlystructured knowledge bases (KBs), which contain prior knowledge about chemicals and diseases. Prior knowledge provides strong support for CDR extraction. How to make full use of it is worth studying.

13p vijisoo2711 27-10-2020 9 1   Download

Automatically understanding chemical-disease relations (CDRs) is crucial in various areas of biomedical research and health care. Supervised machine learning provides a feasible solution to automatically extract relations between biomedical entities from scientific literature, its success, however, heavily depends on large-scale biomedical corpora manually annotated with intensive labor and tremendous investment.

14p vijisoo2711 27-10-2020 16 1   Download

This paper develops a novel method called TDQ to quantify the demethylation epigenetic toxicity, termed the 5-AZA-CdR demethylation toxic equivalency, of aquatic samples from the heavily polluted Bohai Bay using Hep G2 cell lines transiently transfected with the pEGFP-C3 plasmid containing a methylated promoter of the EGFP reporter gene inserted artificially in vitro.

11p viuchiha2711 21-04-2020 12 0   Download