Compared to univariate analysis of genome-wide association (GWA) studies, machine
learning–based models have been shown to provide improved means of learning such multilocus …

Automated annotation of protein function is challenging. As the number of sequenced
genomes rapidly grows, the overwhelming majority of protein products can only be annotated …

Background Lately, there has been a great interest in the application of information extraction
methods to the biomedical domain, in particular, to the extraction of relationships of genes, …

Background A major bottleneck in our understanding of the molecular underpinnings of life
is the assignment of function to proteins. While molecular experiments provide the most …

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global,
community-driven effort to evaluate and improve the computational annotation of protein …

Background Automated extraction of protein-protein interactions (PPI) is an important and
widely studied task in biomedical text mining. We propose a graph kernel based approach for …

Deep learning-based language models pretrained on large unannotated text corpora have
been demonstrated to allow efficient transfer learning for natural language processing, with …

Aim To develop a consensus paper on the central points of an international invitational think‐tank
on nursing and artificial intelligence (AI). Methods We established the Nursing and …

… as it may be that other information is discarded when unifying the corpora, this level of
annotation is also a reflection of the state of the art in biomedical IE methods, and doesn't …

We describe a system for extracting complex events among genes and proteins from biomedical
literature, developed in context of the BioNLP’09 Shared Task on Event Extraction. For …