Mining literature and pathway data to explore the relations of ketamine with neurotransmitters and gut microbiota using a knowledge-graph.
Bioinformatics
; 40(1)2024 01 02.
Article
en En
| MEDLINE
| ID: mdl-38147362
ABSTRACT
MOTIVATION Up-to-date pathway knowledge is usually presented in scientific publications for human reading, making it difficult to utilize these resources for semantic integration and computational analysis of biological pathways. We here present an approach to mining knowledge graphs by combining manual curation with automated named entity recognition and automated relation extraction. This approach allows us to study pathway-related questions in detail, which we here show using the ketamine pathway, aiming to help improve understanding of the role of gut microbiota in the antidepressant effects of ketamine. RESULTS:
The thus devised ketamine pathway 'KetPath' knowledge graph comprises five parts (i) manually curated pathway facts from images; (ii) recognized named entities in biomedical texts; (iii) identified relations between named entities; (iv) our previously constructed microbiota and pre-/probiotics knowledge bases; and (v) multiple community-accepted public databases. We first assessed the performance of automated extraction of relations between named entities using the specially designed state-of-the-art tool BioKetBERT. The query results show that we can retrieve drug actions, pathway relations, co-occurring entities, and their relations. These results uncover several biological findings, such as various gut microbes leading to increased expression of BDNF, which may contribute to the sustained antidepressant effects of ketamine. We envision that the methods and findings from this research will aid researchers who wish to integrate and query data and knowledge from multiple biomedical databases and literature simultaneously. AVAILABILITY AND IMPLEMENTATION Data and query protocols are available in the KetPath repository at https//dx.doi.org/10.5281/zenodo.8398941 and https//github.com/tingcosmos/KetPath.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Microbioma Gastrointestinal
/
Ketamina
Idioma:
En
Revista:
Bioinformatics
/
Bioinformatics (Oxford. Online)
Asunto de la revista:
INFORMATICA MEDICA
Año:
2024
Tipo del documento:
Article