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BACKGROUND Ewing sarcoma family of tumors (ESFT), characterized by t(11;22)(q24;q12), is one of the most common tumors of bone in children and young adults. In addition to EWS/FLI1 gene fusion, copy number changes are known to be significant for the underlying neoplastic development of ESFT and for patient outcome. Our genome-wide high-resolution analysis(More)
We introduce a factor analysis model that summarizes the dependencies between observed variable groups, instead of dependencies between individual variables as standard factor analysis does. A group may correspond to one view of the same set of objects, one of many data sets tied by co-occurrence, or a set of alternative variables collected from statistics(More)
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring data pairs. The model extends the traditional canonical correlation analysis and its probabilistic interpretation in three main ways. First, a full Bayesian treatment enables(More)
Multi-view learning studies how several views, different feature representations , of the same objects could be best utilized in learning. In other words, multi-view learning is analysis of co-occurrence data, where the observations are co-occurrences of samples in the views. Standard multi-view learning such as joint density modeling cannot be done in the(More)
Query formulation and efficient navigation through data to reach relevant results are undoubtedly major challenges for image or video retrieval. Queries of good quality are typically not available and the search process needs to rely on relevance feedback given by the user, which makes the search process iterative. Giving explicit relevance feedback is(More)
We study data fusion under the assumption that data source-specific variation is irrelevant and only shared variation is relevant. Traditionally the shared variation has been sought by maximizing a dependency measure, such as correlation of linear projections in Canonical Correlation Analysis. In this traditional framework it is hard to tackle overfitting(More)
This paper describes Pinview, a content-based image retrieval system that exploits implicit relevance feedback during a search session. The goal is to retrieve interesting images and the relevance feedback could be eye movements or clicks on the images. Pinview contains several novel methods that infer the intent of the user. From relevance feedback and(More)
BACKGROUND Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data analysis. Our focus is on vector-valued data sources, each consisting of measurements of the same entity but on different variables, and on tasks where source-specific variation is(More)