Transformer-based pretrained language models (PLMs) have started a new era in modern
natural language processing (NLP). These models combine the power of transformers …

The rapid development of biomedicine has produced a large number of biomedical written
materials. These unstructured text data create serious challenges for biomedical …

Background Recently, food science has been garnering a lot of attention. There are many
open research questions on food interactions, as one of the main environmental factors, with …

In the modern era of big data, one of the biggest challenges is to find an efficient way of
extracting information from unstructured data and structuring it in a form that can be …

Finding relations between genes and diseases is essential in develo** a clinical
diagnosis, treatment, and drug design for diseases. One successful approach for mining the …

Despite the abundance of genotype-phenotype association studies, the resulting
association outcomes often lack robustness and interpretations. To address these …

It is vital to investigate the complex mechanisms underlying tumors to better understand
cancer and develop effective treatments. Metabolic abnormalities and clinical phenotypes …

Gene-disease association plays a crucial role in healthcare knowledge discovery, and a
large amount of valuable information is hidden in the literature. To alleviate this problem, we …

Genes and proteins constitute the fundamental entities of molecular genetics. We here
introduce ProGene (formerly called FSU-PRGE), a corpus that reflects our efforts to cope …

Bridging heterogeneous mutation data fills in the gap between various data categories and
propels discovery of disease-related genes. It is known that genome-wide association study …