Projects such as the European Covid-19 Forecast Hub publish forecasts on the national level for new deaths, new cases, and hospital admissions, but not direct measurements of hospital strain like critical care bed occupancy at the sub-national level, which is of particular interest to health professionals for planning purposes. We present a sub-national French framework for forecasting hospital strain based on a non-Markovian compartmental model, its associated online visualisation tool and a retrospective evaluation of the real-time forecasts it provided from January to December 2021 by comparing to three baselines derived from standard statistical forecasting methods (a naive model, auto-regression, and an ensemble of exponential smoothing and ARIMA). In terms of median absolute error for forecasting critical care unit occupancy at the two-week horizon, our model only outperformed the naive baseline for 4 out of 14 geographical units and underperformed compared to the ensemble baseline for 5 of them at the 90% confidence level (n = 38). However, for the same level at the 4 week horizon, our model was never statistically outperformed for any unit despite outperforming the baselines 10 times spanning 7 out of 14 geographical units. This implies modest forecasting utility for longer horizons which may justify the application of non-Markovian compartmental models in the context of hospital-strain surveillance for future pandemics.

BACKGROUND: Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation. Although the principles of the analysis of reporter gene data are well-established today, there is a lack of general-purpose bioinformatics tools based on generic measurement models and sound inference procedures. This has motivated the development of WellInverter, a web application based on well-known methods for regularized linear inversion. RESULTS: We present a new version of WellInverter that considerably improves the performance and usability of the original application. In particular, we have put in place a parallel computing architecture with a load balancer to distribute analysis queries over several back-end servers, we have completely redesigned the graphical user interface to better support the different analysis steps, and we have developed a plug-in system for the parsing of data files produced by microplate readers from different manufacturers. We illustrate the functioning of WellInverter by analyzing data of the expression of a fluorescent reporter gene controlled by a phage promoter in growing Escherichia coli populations. We show that the expression pattern in different growth media, supporting different growth rates, corresponds to the pattern expected for a constitutive gene. CONCLUSIONS: The new version of WellInverter is a robust, easy-to-use and scalable web application, which has been deployed on two publicly accessible web servers and which can also be installed locally. A demo version of the application with two sample datasets is available on-line.

DevOps teams have to consider many technology and platform aspects when developing, deploying and operating cloud based applications: application deployments need to work everywhere on different cloud platforms, identities need to come from anywhere, and networks need to connect to anyone. The CYCLONE middleware is a holistic middleware stack that allows deploying and managing cloud based applications on multiple clouds and multiple cloud platforms. It includes a deployment manager, a practical identity federation, as well as a network manager that connects VMs independent of any specific infrastructure. This article explains the CYCLONE middleware stack, and what it can offer for application developers and operators. The paper describes in details the main bioinformatics use cases that evolve from a single VM installation for simple microbial research to multicloud infrastructure for advanced genomic resource. The paper also describes the CYCLONE federated identity management and access control infrastructure that significantly simplifies access for institutional users.

Cloud infrastructures provide compelling features for scientific and engineering applications. Federated clouds additionally promise improved scalability via access to a larger pool of resources and improved service availability through geographically distributed redundant servers. Effective use of federated clouds requires the creation of portable appliances and consistent appliance management techniques. The Stratus Lab Marketplace, a platform-agnostic appliance registry, facilitates appliance management in a federated environment. This paper describes the Marketplace design goals, implementation, and security concerns. It also covers the planned improvements based on our experience of running this service in production for more than two years.

MOTIVATION: Methods for automatic nuclear magnetic resonance (NMR) structure determination need to face a high level of ambiguity encountered in NMR spectra recorded by solid-state NMR and by solution NMR of partially unfolded proteins, leading to time-consuming calculations. The software package Ambiguous Restraints for Iterative Assignment (ARIA) allows for straightforward parallelization of the calculation, as the conformers can be generated in parallel on many nodes. RESULTS: Due to its architecture, the adaptation of ARIA to grid computing can be easily achieved by using the middleware glite and JDL (Job Description Language) scripts. This adaptation makes it possible to address highly ambiguous datasets, because of the much larger conformational sampling that can be generated by use of the grid computational power. AVAILABILITY: The version 2.3.1 of ARIA implemented on the grid is freely available from the ARIA web site: aria.pasteur.fr/downloads.

We propose an algorithm for checking the semantic compatibility of Web service parameters and for suggesting compatible parameters pairings between two Web services semi-automatically. This algorithm supports semi-automatic Web service composition in workflows where the order of the Web service is known. In our use case, we used the OWL-S semantic description of Web service. We automatically generated a Taverna-compatible Xscufl file whenever possible.

MOTIVATION: The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. RESULTS: BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. AVAILABILITY: The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community.

Bioinformatics needs high-throughput computing and huge data storage to understand datasets such as ones produced by complete genome projects. But these data are linked to patients, and used in scientific or industrial processes such as drug design and gene function identification. These use cases need to have a certain level of confidentiality and integrity to preserve the patient privacy or the patent secret. Obviously important in a local computing context such as supercomputer or cluster, these requirements are exarcebated in the context of a grid such EGEE, where the computing and storage resources are distributed across a worldwide platform. We have developed the EncFile encrypted files management system, deployed on the production platform of the EGEE project, and associated to encrypted representative biological resources. Thus we provided grid users with a user-friendly component that doesn't require any user privileges. Moreover, our EncFile system can be also deployed on other distributed systems as it is not linked to the EGEE grid components.

UNLABELLED: MPSA is a stand-alone software intended to protein sequence analysis with a high integration level and Web clients/server capabilities. It provides many methods and tools, which are integrated into an interactive graphical user interface. It is available for most Unix/Linux and non-Unix systems. MPSA is able to connect to a Web server (e.g. http://pbil.ibcp.fr/NPSA) in order to perform large-scale sequence comparison on up-to-date databanks. AVAILABILITY: Free to academic http://www.ibcp.fr/mpsa/ CONTACT: [email protected]