An ontology based method to solve query identifier heterogeneity in post-genomic clinical trials.
The increasing amount of information available for biomedical research has led to issues related to knowledge discovery in large collections of data. Moreover, Information Retrieval techniques must consider heterogeneities present in databases, initially belonging to different domains-e.g. clinical and genetic data. One of the goals, among others, of the ACGT European is to provide seamless and homogeneous access to integrated databases. In this work, we describe an approach to overcome heterogeneities in identifiers inside queries. We present an ontology classifying the most common identifier semantic heterogeneities, and a service that makes use of it to cope with the problem using the described approach. Finally, we illustrate the solution by analysing a set of real queries.
Anguita
Alberto
A
Biomedical Informatics Group, Artificial Intelligence Laboratory, School of Computer Science, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, 28660 Boadilla del Monte, Madrid, Spain.
Martín
Luis
L
Crespo
José
J
Tsiknakis
Manolis
M
D000465:Algorithms; D003628:Database Management Systems; D030541:Databases, Genetic; D016678:Genome; D006801:Humans; D007256:Information Systems; D016490:Integrated Advanced Information Management Systems; D008491:Medical Informatics Applications; D016347:Medical Records Systems, Computerized; D015337:Multicenter Studies as Topic; D009369:Neoplasms / Q000235:genetics* / Q000628:therapy; D012660:Semantics; D012984:Software; D018875:Vocabulary, Controlled