TY - JOUR
T1 - Yeast Knowledge Graphs Database for Exploring Saccharomyces Cerevisiae and Schizosaccharomyces Pombe
T2 - Yeast Knowledge Graphs for Saccharomyces and Pombe
AU - Kumar, Mani R.
AU - Arulprakasam, Karthick Raja
AU - Kutevska, An Nikol
AU - Mutwil, Marek
AU - Thibault, Guillaume
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025
Y1 - 2025
N2 - Biomedical literature contains an extensive wealth of information on gene and protein function across various biological processes and diseases. However, navigating this vast and often restricted-access data can be challenging, making it difficult to extract specific insights efficiently. In this study, we introduce a high-throughput pipeline that leverages OpenAI's Generative Pre-Trained Transformer Model (GPT) to automate the extraction and analysis of gene function information. We applied this approach to 84,427 publications on Saccharomyces cerevisiae and 6,452 publications on Schizosaccharomyces pombe, identifying 3,432,749 relationships for budding yeast and 421,198 relationships for S. pombe. This resulted in a comprehensive, searchable online Knowledge Graph database, available at yeast.connectome.tools and spombe.connectome.tools, which offers users extensive access to various interactions and pathways. Our analysis underscores the power of integrating artificial intelligence with bioinformatics, as demonstrated through key insights into important nodes like Hsp104 and Atg8 proteins. This work not only facilitates efficient data extraction in yeast research but also presents a scalable model for similar studies in other biological systems.
AB - Biomedical literature contains an extensive wealth of information on gene and protein function across various biological processes and diseases. However, navigating this vast and often restricted-access data can be challenging, making it difficult to extract specific insights efficiently. In this study, we introduce a high-throughput pipeline that leverages OpenAI's Generative Pre-Trained Transformer Model (GPT) to automate the extraction and analysis of gene function information. We applied this approach to 84,427 publications on Saccharomyces cerevisiae and 6,452 publications on Schizosaccharomyces pombe, identifying 3,432,749 relationships for budding yeast and 421,198 relationships for S. pombe. This resulted in a comprehensive, searchable online Knowledge Graph database, available at yeast.connectome.tools and spombe.connectome.tools, which offers users extensive access to various interactions and pathways. Our analysis underscores the power of integrating artificial intelligence with bioinformatics, as demonstrated through key insights into important nodes like Hsp104 and Atg8 proteins. This work not only facilitates efficient data extraction in yeast research but also presents a scalable model for similar studies in other biological systems.
KW - bioinformatics
KW - knowledge graph
KW - Saccharomyces
KW - Schizosaccharomyces
KW - yeast
U2 - 10.1016/j.jmb.2025.169072
DO - 10.1016/j.jmb.2025.169072
M3 - Journal article
C2 - 40057225
AN - SCOPUS:86000753954
SN - 0022-2836
VL - 437
JO - Journal of Molecular Biology
JF - Journal of Molecular Biology
IS - 10
M1 - 169072
ER -