With the development of new experimental technologies, biologists are faced with an avalanche of data to be computationally analyzed for scientific advancements and discoveries to emerge. Faced with the complexity of analysis pipelines, the large number of computational tools, and the enormous amount of data to manage, there is compelling evidence that many if not most scientific discoveries will not stand the test of time: increasing the reproducibility of computed results is of paramount importance. The objective we set out in this paper is to place scientific workflows in the context of reproducibility. To do so, we define several kinds of reproducibility that can be reached when scientific workflows are used to perform experiments. We characterize and define the criteria that need to be catered for by reproducibility-friendly scientific workflow systems, and use such criteria to place several representative and widely used workflow systems and companion tools within such a framework. We also discuss the remaining challenges posed by reproducible scientific workflows in the life sciences. Our study was guided by three use cases from the life science domain involving in silico experiments. (Résumé d'auteur

This paper presents the Virtual Imaging Platform (VIP), a platform accessible at http://vip.creatis.insa-lyon.fr to facilitate the sharing of object models and medical image simulators, and to provide access to distributed computing and storage resources. A complete overview is presented, describing the ontologies designed to share models in a common repository, the workflow template used to integrate simulators, and the tools and strategies used to exploit computing and storage resources. Simulation results obtained in four image modalities and with different models show that VIP is versatile and robust enough to support large simulations. The platform currently has 200 registered users who consumed 33 years of CPU time in 2011.

Abstract. Aspect-Oriented Modeling (AOM) approaches propose to model reusable aspects, or cross-cutting concerns, that can be composed in different systems at a model or code level. Building complex systems with reusable aspects helps managing software complexity. But in general, reusability of an aspect is limited to a particular context. On the one hand, if the target model does not match the template point-to-point, the aspect cannot be applied. On the other hand, even when it is actually applied, it is woven into the target model always in the same way. In this paper 1 , we point out the needs of variability in the AOM approaches and introduce seamless variability mechanisms in an existing AOM approach to improve reusability. Our aspects can fit various contexts and can be composed into the base model in different ways. Introducing variability into AOM approaches will turn standard aspects into highly reusable aspects.

BackgroundHuman myeloma cell lines (HMCLs) are widely used for their representation of primary myeloma cells because they cover patient diversity, although not fully. Their genetic background is mostly undiscovered, and no comprehensive study has ever been conducted in order to reveal those details.MethodsWe performed whole-exon sequencing of 33 HMCLs, which were established over the last 50 years in 12 laboratories. Gene expression profiling and drug testing for the 33 HMCLs are also provided and correlated to exon-sequencing findings.ResultsMissense mutations were the most frequent hits in genes (92%). HMCLs harbored between 307 and 916 mutations per sample, with TP53 being the most mutated gene (67%). Recurrent bi-allelic losses were found in genes involved in cell cycle regulation (RB1, CDKN2C), the NFκB pathway (TRAF3, BIRC2), and the p53 pathway (TP53, CDKN2A). Frequency of mutations/deletions in HMCLs were either similar to that of patients (e.g., DIS3, PRDM1, KRAS) or highly increased (e.g., TP53, CDKN2C, NRAS, PRKD2). MAPK was the most altered pathway (82% of HMCLs), mainly by RAS mutants. Surprisingly, HMCLs displayed alterations in epigenetic (73%) and Fanconi anemia (54%) and few alterations in apoptotic machinery. We further identified mutually exclusive and associated mutations/deletions in genes involved in the MAPK and p53 pathways as well as in chromatin regulator/modifier genes. Finally, by combining the gene expression profile, gene mutation, gene deletion, and drug response, we demonstrated that several targeted drugs overcome or bypass some mutations.ConclusionsWith this work, we retrieved genomic alterations of HMCLs, highlighting that they display numerous and unprecedented abnormalities, especially in DNA regulation and repair pathways. Furthermore, we demonstrate that HMCLs are a reliable model for drug screening for refractory patients at diagnosis or at relapse.Electronic supplementary materialThe online version of this article (10.1186/s13045-018-0679-0) contains supplementary material, which is available to authorized users.

The development of scientific workflows is evolving towards the systematic use of service oriented architectures, enabling the composition of dedicated and highly parameterized software services into processing pipelines. Building consistent workflows then becomes a cumbersome and error-prone activity as users cannot manage such large scale variability. This paper presents a rigorous and tooled approach in which techniques from Software Product Line (SPL) engineering are reused and extended to manage variability in service and workflow descriptions. Composition can be facilitated while ensuring consistency. Services are organized in a rich catalog which is organized as a SPL and structured according to the common and variable concerns captured for all services. By relying on sound merging techniques on the feature models that make up the catalog, reasoning about the compatibility between connected services is made possible. Moreover, an entire workflow is then seen as a multiple SPL (i.e., a composition of several SPLs). When services are configured within, the propagation of variability choices is then automated with appropriate techniques and the user is assisted in obtaining a consistent workflow. The approach proposed is completely supported by a combination of dedicated tools and languages. Illustrations and experimental validations are provided using medical imaging pipelines, which are representative of current scientific workflows in many domains.

Querying and linking distributed and heterogeneous databases is increasingly needed, as plentiful data resources are published over the Web. This work describes the design of a versatile query system named KGRAM that supports (i) multiple query languages among which the SPARQL 1.1 standard, (ii) federation of multiple heterogeneous and distributed data sources, and (iii) adaptability to various data manipulation use cases. KGRAM provides abstractions for both the query language and the data model, thus delivering unifying reasoning mechanisms. It is implemented as a modular software suite to ease architecting and deploying dedicated data manipulation platforms. Its design integrates optimization concerns to deliver high query performance. Both KGRAM's software versatility and performance are evaluated.

This paper describes the creation of a comprehensive conceptualization of object models used in medical image simulation, suitable for major imaging modalities and simulators. The goal is to create an application ontology that can be used to annotate the models in a repository integrated in the Virtual Imaging Platform (VIP), to facilitate their sharing and reuse. Annotations make the anatomical, physiological and pathophysiological content of the object models explicit. In such an interdisciplinary context we chose to rely on a common integration framework provided by a foundational ontology, that facilitates the consistent integration of the various modules extracted from several existing ontologies, i.e. FMA, PATO, MPATH, RadLex and ChEBI. Emphasis is put on methodology for achieving this extraction and integration. The most salient aspects of the ontology are presented, especially the organization in model layers, as well as its use to browse and query the model repository.

Our protocol has many assets. A nationwide recruitment allows for the inclusion of large pedigrees with familial forms of IA. It will combine accurate phenotyping and comprehensive imaging with high-throughput genetic screening. Last, it will enable exploiting metadata to explore new pathophysiological pathways of interest by crossing clinical, genetic, biological, and imaging information.