Information Extraction from Bibliography for Marker-Assisted Selection in Wheat

Improvement of most animal and plant species of agronomical interest in the near future has become an international stake because of the increasing demand for feeding a growing world population and to mitigate the reduction of the industrial resources. The recent advent of genomic tools contributed to improve the discovery of linkage between molecular markers and genes that are involved in the control of traits of agronomical interest such as grain number or disease resistance. This information is mostly published as scientific papers but rarely available in databases. Here, we present a method aiming at automatically extract this information from the scientific literature and relying on a knowledge model of the target information and on the WheatPhenotype ontology that we developed for this purpose. The information extraction results were evaluated and integrated into the on-line semantic search engine AlvisIR WheatMarker.