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Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins(More)
In recent years, ontologies have become a mainstream topic in biomedical research. When biological entities are described using a common schema, such as an ontology, they can be compared by means of their annotations. This type of comparison is called semantic similarity, since it assesses the degree of relatedness between two entities by the similarity in(More)
BACKGROUND Several semantic similarity measures have been applied to gene products annotated with Gene Ontology terms, providing a basis for their functional comparison. However, it is still unclear which is the best approach to semantic similarity in this context, since there is no conclusive evaluation of the various measures. Another issue, is whether(More)
Motivation: While several efforts have been made in measuring GO-based protein semantic similarity, it is still unclear which are the best approaches to measure it and furthermore whether electronic annotations should be used. Results: We studied the behaviour of 8 distinct semantic similarity measures as function of sequence similarity with and without(More)
Bioinformatics arose from the need to manage and extract knowledge from the vast amount of sequence data generated by automated Molecular Biology techniques. One important step for this was the development of the Gene Ontol-ogy (GO), which provided a unified and structured vocabulary to describe proteins, and also a background to compare them, contributing(More)
Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the(More)
AgreementMakerLight (AML) is an automated ontology matching framework based on element-level matching and the use of external resources as background knowledge. This paper describes the configuration of AML for the OAEI 2014 competition and discusses its results. Our goal this year was broadening the scope of AML by delving into aspects such as translation(More)
AgreementMaker is one of the leading ontology matching systems, thanks to its combination of a flexible and extensible framework with a comprehensive user interface. In many domains, such as the biomedical, ontologies are becoming increasingly large thus presenting new challenges. We have developed a new core framework, Agreement-MakerLight, focused on(More)
Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of(More)
The application of semantic similarity measures to proteins annotated with Gene Ontology terms has become a common method in bioinformatics. However, the evaluation of these measures is still challenging, since no common standard of evaluation exists. We present an online tool for the automated evaluation of GO-based semantic similarity measures, CESSM,(More)