Recent advances in sequencing, mass spectrometry and cytometry technologies have enabled researchers to collect large-scale omics data from the same set of biological samples. The joint analysis of multiple omics offers the opportunity to uncover coordinated cellular processes acting across different omic layers. In this work, we present a thorough comparison of a selection of recent integrative clustering approaches, including Bayesian (BCC and MDI) and matrix factorization approaches (iCluster, moCluster, JIVE and iNMF). Based on simulations, the methods were evaluated on their sensitivity and their ability to recover both the correct number of clusters and the simulated clustering at the common and data-specific levels. Standard non-integrative approaches were also included to quantify the added value of integrative methods. For most matrix factorization methods and one Bayesian approach (BCC), the shared and specific structures were successfully recovered with high and moderate accuracy, respectively. An opposite behavior was observed on non-integrative approaches, i.e. high performances on specific structures only. Finally, we applied the methods on the Cancer Genome Atlas breast cancer data set to check whether results based on experimental data were consistent with those obtained in the simulations.
Abstract-For each kind of distributed computing infrastructures, i.e., clusters, grids, clouds, data centers, or supercomputers, storage is a essential component to cope with the tremendous increase in scientific data production and the ever-growing need for data analysis and preservation. Understanding the performance of a storage subsystem or dimensioning it properly is an important concern for which simulation can help by allowing for fast, fully repeatable, and configurable experiments for arbitrary hypothetical scenarios. However, most simulation frameworks tailored for the study of distributed systems offer no or little abstractions or models of storage resources.In this paper, we detail the extension of SimGrid, a versatile toolkit for the simulation of large-scale distributed computing systems, with storage simulation capacities. We first define the required abstractions and propose a new API to handle storage components and their contents in SimGrid-based simulators. Then we characterize the performance of the fundamental storage component that are disks and derive models of these resources. Finally we list several concrete use cases of storage simulations in clusters, grids, clouds, and data centers for which the proposed extension would be beneficial.
Grid operators in EGEE have been using a dedicated dashboard as their central operational tool, stable and scalable for the last 5 years despite continuous upgrade from specifications by users, monitoring tools or data providers. In EGEE-III, recent regionalisation of operations led the Operations Portal developers to conceive a standalone instance of this tool. We will see how the dashboard reorganization paved the way for the re-engineering of the portal itself. The outcome is an easily deployable package customized with relevant information sources and specific decentralized operational requirements. This package is composed of a generic and scalable data access mechanism, Lavoisier; a renowned php framework for configuration flexibility, Symfony and a MySQL database. VO life cycle and operational information, EGEE broadcast and Downtime notifications are next for the major reorganization until all other key features of the Operations Portal are migrated to the framework. Features specifications will be sketched at the same time to adapt to EGI requirements and to upgrade. Future work on feature regionalisation, on new advanced features or strategy planning will be tracked in EGI-Inspire through the Operations Tools Advisory Group, OTAG, where all users, customers and third parties of the Operations Portal are represented from January 2010.
This paper deals with the lowest levels of small streams in a southern Touraine plateau area which froms of ho- mogenous whole. Their drainage basins vary from 80 to 109 km2 in superficy. The are little streams with modest flow whose régime is characterized by high water levels from november to april or may, followed by an intermediate stage gradually leading to the summer low water level. Their lowest water levels are thus dépendent as well on the dry months (according to P. Birot's formula : P < 4 T) which vary in number and grouping from year to year, as on the correlated pulsations in the annual flow esta- blished according to Thornthwaite's formula. In this case the annual flow is characterized mainly by high levels in winter and shrinkage in the summer months during which lowest levels are recorded. The latter vary from year to year and occur either in july, august, or september and more rarely in october. Variations in lowest water level characteristics from one stream to another are due to différences in basin area and interannual weather type changes which are mostly noted from august on.
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