Finding relevant publications in the large and rapidly growing body of biomedical literature is challenging. Search queries on PubMed often return thousands of publications and it ...
Background: Automated information extraction from biomedical literature is important because a vast amount of biomedical literature has been published. Recognition of the biomedic...
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which a...
Irena Spasic, Sophia Ananiadou, John McNaught, Ana...
Most knowledge accumulated through scientific discoveries in genomics and related biomedical disciplines is buried in the vast amount of biomedical literature. Since understandin...
: The biomedical literature is growing at an ever-increasing rate, which pronounces the need to support scientists with advanced, automated means of accessing knowledge. We investi...
Background: The construction of literature-based networks of gene-gene interactions is one of the most important applications of text mining in bioinformatics. Extracting potentia...
Background: The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data min...
We propose an approach for extracting relations between entities from biomedical literature based solely on shallow linguistic information. We use a combination of kernel function...
The explosive growth in the biomedical literature has made it difficult for researchers to keep up with advancements, even in their own narrow specializations. In addition, this c...