Prosemantic features for content-based image retrieval

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-18449-9_8Revised Selected Papers of 7th International Workshop, AMR 2009, Madrid, Spain, September 24-25, 2009We present here, an image description approach based on prosemantic features. The images are represented by a set of low-level features related to their structure and color distribution. Those descriptions are fed to a battery of image classifiers trained to evaluate the membership of the images with respect to a set of 14 overlapping classes. Prosemantic features are obtained by packing together the scores. To verify the effectiveness of the approach, we designed a target search experiment in which both low-level and prosemantic features are embedded into a content-based image retrieval system exploiting relevance feedback. The experiments show that the use of prosemantic features allows for a more successful and quick retrieval of the query images

BBMS + + – basic bioinformatics meta-searcher

In this paper we present a Basic Bioinformatics Meta-searcher (BBMS), a web-based service aiming to simplify and integrate biological data searching through selected biological databases. BBMS facilitates biological data searching enabling multiple sources transparently, increasing research productivity as it avoids time consuming learning and parameterization of different search engines. As a complementary service, BBMS provides insight and links to common online bioinformatics tools. Users’ feedback when evaluating BBMS in terms of usability, usefulness and efficiency was very positive

ImageCLEF 2014: Overview and analysis of the results

This paper presents an overview of the ImageCLEF 2014 evaluation lab. Since its first edition in 2003, ImageCLEF has become one of the key initiatives promoting the benchmark evaluation of algorithms for the annotation and retrieval of images in various domains, such as public and personal images, to data acquired by mobile robot platforms and medical archives. Over the years, by providing new data collections and challenging tasks to the community of interest, the ImageCLEF lab has achieved an unique position in the image annotation and retrieval research landscape. The 2014 edition consists of four tasks: domain adaptation, scalable concept image annotation, liver CT image annotation and robot vision. This paper describes the tasks and the 2014 competition, giving a unifying perspective of the present activities of the lab while discussing future challenges and opportunities.This work has been partially supported by the tranScriptorium FP7 project under grant #600707 (M. V., R. 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Exploring and challenging the network of angiogenesis

Angiogenesis is one of the hallmarks of cancer and, as such, one of the alternative general targets for anticancer therapy. Since angiogenesis is a complex process involving a high number of interconnected components, a network approach would be a convenient systemic way to analyse responses to directed drug attacks. Herein we show that, although the angiogenic network is easily broken by short combinations of directed attacks, it still remains essentially functional by keeping the global patterns and local efficiency essentially unaltered after these attacks. This is a clear sign of its high robustness and resilience and stresses the need of directed, combined attacks for an effective blockade of the process. The results of this theoretical study could be relevant for the design of new antiangiogenic therapies and the selection of their targets

Towards an Evolutionary Model of Transcription Networks

DNA evolution models made invaluable contributions to comparative genomics, although it seemed formidable to include non-genomic features into these models. In order to build an evolutionary model of transcription networks (TNs), we had to forfeit the substitution model used in DNA evolution and to start from modeling the evolution of the regulatory relationships. We present a quantitative evolutionary model of TNs, subjecting the phylogenetic distance and the evolutionary changes of cis-regulatory sequence, gene expression and network structure to one probabilistic framework. Using the genome sequences and gene expression data from multiple species, this model can predict regulatory relationships between a transcription factor (TF) and its target genes in all species, and thus identify TN re-wiring events. Applying this model to analyze the pre-implantation development of three mammalian species, we identified the conserved and re-wired components of the TNs downstream to a set of TFs including Oct4, Gata3/4/6, cMyc and nMyc. Evolutionary events on the DNA sequence that led to turnover of TF binding sites were identified, including a birth of an Oct4 binding site by a 2nt deletion. In contrast to recent reports of large interspecies differences of TF binding sites and gene expression patterns, the interspecies difference in TF-target relationship is much smaller. The data showed increasing conservation levels from genomic sequences to TF-DNA interaction, gene expression, TN, and finally to morphology, suggesting that evolutionary changes are larger at molecular levels and smaller at functional levels. The data also showed that evolutionarily older TFs are more likely to have conserved target genes, whereas younger TFs tend to have larger re-wiring rates

On the coöperative creation of multimedia meaning

The final publication is available at Springer via http://dx.doi.org/110.1007/978-3-642-10543-2_5Proceedings of 4th International Conference on Semantic and Digital Media Technologies, SAMT 2009 Graz, Austria, December 2-4, 2009In this paper, we propose a content-based method the for semi- automatic organization of photo albums based on the analysis of how different users organize their own pictures. The goal is to help the user in dividing his pictures into groups characterized by a similar semantic content. The method is semi-automatic: the user starts to assign labels to the pictures and unlabeled pictures are tagged with proposed labels. The user can accept the recommendation or make a correction. The method is conceptually articulated in two parts. First, we use a suitable feature representation of the images to model the different classes that the users have collected, second, we look for correspondences between the criteria used by the different users. A quantitative evaluation of the proposed approach is proposed based on pictures of a set of members of the flickr® photo-sharing community