TY - JOUR
T1 - PlantConnectome
T2 - A knowledge graph database encompassing >71,000 plant articles
AU - Lim, Shan Chun
AU - Itharajula, Manoj
AU - Møller, Mads Harder
AU - Sunil, Rohan Shawn
AU - Fo, Kevin
AU - Chuah, Yu Song
AU - Foo, Herman
AU - Davey, Emilia Emmanuelle
AU - Fullwood, Melissa
AU - Thibault, Guillaume
AU - Mutwil, Marek
N1 - Publisher Copyright:
© 2025 The Author(s).
PY - 2025/7/1
Y1 - 2025/7/1
N2 - One of the main quests in plant biology is understanding how gene products and metabolites work together to form complex networks that drive plant development and responses to environmental stimuli. However, the ever-growing volume and diversity of scientific literature make it increasingly challenging to stay current with the latest advances in functional genetics studies. Here, we tackled this challenge by deploying the text-mining capacities of large language models to process over 71,000 plant biology abstracts. Our approach presents nearly 5 million functional relationships between 2.4 million biological entities-genes or gene products, metabolites, tissues, and others-with a high accuracy of over 85%. We encapsulated these findings in the user-friendly database PlantConnectome and demonstrated its diverse utility by providing insights into gene regulatory networks, protein-protein interactions, and stress responses. We believe this innovative use of artificial intelligence (AI) in the life sciences will allow plant scientists to keep up to date with the rapidly growing corpus of scientific literature. PlantConnectome is available at https://plant.connectome.tools/.
AB - One of the main quests in plant biology is understanding how gene products and metabolites work together to form complex networks that drive plant development and responses to environmental stimuli. However, the ever-growing volume and diversity of scientific literature make it increasingly challenging to stay current with the latest advances in functional genetics studies. Here, we tackled this challenge by deploying the text-mining capacities of large language models to process over 71,000 plant biology abstracts. Our approach presents nearly 5 million functional relationships between 2.4 million biological entities-genes or gene products, metabolites, tissues, and others-with a high accuracy of over 85%. We encapsulated these findings in the user-friendly database PlantConnectome and demonstrated its diverse utility by providing insights into gene regulatory networks, protein-protein interactions, and stress responses. We believe this innovative use of artificial intelligence (AI) in the life sciences will allow plant scientists to keep up to date with the rapidly growing corpus of scientific literature. PlantConnectome is available at https://plant.connectome.tools/.
UR - http://www.scopus.com/inward/record.url?scp=105011876675&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=105011876675&partnerID=8YFLogxK
U2 - 10.1093/plcell/koaf169
DO - 10.1093/plcell/koaf169
M3 - Article
AN - SCOPUS:105011876675
SN - 1040-4651
VL - 37
JO - Plant Cell
JF - Plant Cell
IS - 7
M1 - koaf169
ER -