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A key requirement for precision medicine is the accurate identification of patients that would respond to a specific treatment or those that represent a high-risk group, and a plethora of molecular biomarkers have been proposed for this purpose during the last decade. Their application in clinical settings, however, is not always straightforward due to relatively high costs of some tests, limited availability of the biological material and time, and procedural constraints. Hence, there is an increasing interest in constructing tissue-based surrogate biomarkers that could be applied with minimal overhead directly to histopathology images and which could be used for guiding the selection of eventual further molecular tests. In the context of colorectal cancer, we present a method for constructing a surrogate biomarker that is able to predict with high accuracy whether a sample belongs to the “BRAF-positive” group, a high-risk group comprising V600E BRAF mutants and BRAF-mutant-like tumors. Our model is trained to mimic the predictions of a 64-gene signature, the current definition of BRAF-positive group, thus effectively identifying histopathology image features that can be linked to a molecular score. Since the only required input is the routine histopathology image, the model can easily be integrated in the diagnostic workflow. [ABSTRACT FROM AUTHOR]

* Premise of the study: Red clover (Trifolium pratense) is an important forage plant from the legume family with great importance in agronomy and livestock nourishment. Nevertheless, assembling its medium-sized genome presents a challenge, given current hardware and software possibilities. Next-generation sequencing technologies enable us to generate large amounts of sequence data at low cost. In this study, the genome assembly and red clover genome features are presented. * Methods: First, assembly software was assessed using data sets from a closely related species to find the best possible combination of assembler plus error correction program to assemble the red clover genome. The newly sequenced genome was characterized by repetitive content, number of protein-coding and nonprotein-coding genes, and gene families and functions. Genome features were also compared with those of other sequenced plant species. * Key results: Abyss with Echo correction was used for de novo assembly of the red clover genome. The presented assembly comprises -314.6 Mbp. In contrast to leguminous species with comparable genome sizes, the genome of T. pratense contains a larger repetitive portion and more abundant retrotransposons and DNA transposons. Overall, 47 398 protein-coding genes were annotated from 64 761 predicted genes. Comparative analysis revealed several gene families that are characteristic for T. pratense. Resistance genes, leghemoglobins, and nodule-specific cystein-rich peptides were identified and compared with other sequenced species. * Conclusions: The presented red clover genomic data constitute a resource for improvement through molecular breeding and for comparison to other sequenced plant species. [ABSTRACT FROM AUTHOR]

Job Provenance (JP), part of the gLite Grid middleware, is a service that keeps long-term trace on completed computations for further reference. It is a job-centric service, keeping records about job life cycle, its environment, inputs/outputs, user parameters, and annotations. During the first provenance challenge, we explored the relation between a specific job-centric Grid-oriented provenance and a more general data provenance approach. The challenge represents a use case which emphasizes fields that were not priorities in the original JP design. However, we proved that the design is sufficiently general to cope with this mode of use. We also identified several areas where it is feasible to extend the current implementation. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]