UNLABELLED: Yale Image Finder (YIF) is a publicly accessible search engine featuring a new way of retrieving biomedical images and associated papers based on the text carried inside the images. Image queries can also be issued against the image …
We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; http://bcms.bioinfo.cnio.es/). This prototype platform is a joint effort of 13 research groups and provides automatically generated …
BACKGROUND: The goal of the gene normalization task is to link genes or gene products mentioned in the literature to biological databases. This is a key step in an accurate search of the biological literature. It is a challenging task, even for the …
MOTIVATION: Proteomics researchers need to be able to quickly retrieve relevant information from the web and the biomedical literature. To improve information retrieval, we leverage the structure of the semantic web, developing an approach for …
BACKGROUND: Nicotine dependence (ND) is costly to societies worldwide, moderately heritable, and genetically complex. Risk loci can be identified with genetic linkage analysis independent of prior physiological hypotheses. METHODS: We completed a …
The Biology of Addictive Diseases-Database (BiolAD-DB) system is a research bioinformatics system for archiving, analyzing, and processing of complex clinical and genetic data. The database schema employs design principles for handling complex …
INTRODUCTION: In this work, we introduce the concept of semantic role labeling to the medical domain. We report first results of porting and adapting an existing resource, Propbank, to the medical field. Propbank is an adjunct to Penn Treebank that …
Sophisticated information technologies are needed for effective data acquisition and integration from a growing body of the biomedical literature. Successful term identification is key to getting access to the stored literature information, as it is …
Information on molecular networks, such as networks of interacting proteins, comes from diverse sources that contain remarkable differences in distribution and quantity of errors. Here, we introduce a probabilistic model useful for predicting protein …
The immense growth in the volume of research literature and experimental data in the field of molecular biology calls for efficient automatic methods to capture and store information. In recent years, several groups have worked on specific problems …