H : Biological knowledge discovery from data , texts and bio-images H 01 :

Genomic islands (GIs) in bacteria are commonly associated with their rapid environmental adaptation, including their pathogenicity. This amplifies the importance of the ability to accurately detect GIs in bacteria. The Pre_GI database is a web based platform which forms part of the SeqWord project and contains 26 744 GIs predicted by SWGIS program in 2407 bacterial chromosomes and plasmids. SWGIS is a composition based GI identifier and quite often ribosomal RNA operons (rrn) characterized by an alternative oligonucleotide usage are recognized by this program as GIs. Consequently, 4473 predicted GIs from 1344 replicons were initially discarded and deemed as false positives due to the presence of 16S RNA‘s as rrn operons are believed to be resistant to horizontal transfer. However, recent publications showed that the horizontal rrn transfer cannot be excluded. We investigated the discarded regions for the presence of genetic markers of true GIs and evaluated the distribution of such insertion sites. H02: Sylvain Demey, Evelyne Begaud, Nahla Chaïbi, Jean-Mary Gallais, Elodie RaynalMelchy, Loïc Talignani, Emmanuelle Helloin, Serge Casaregola, Anne Favel, Martial Briand, Florence Valence-Bertel, Marie-Laure Dardé, Isabelle Villena, Rémy Guyoneaud, Michaël Pressigout and Chantal Bizet. BRC-LIMS : application for the management of French Biological Resource Centres of Microorganisms Abstract: Introduction: The operation and development of Biological Resource Centres (BRCs) make necessary the use of software to manage all data relating to acquisition, characterization, production, storage as well as distribution of biological resources. Currently, Introduction: The operation and development of Biological Resource Centres (BRCs) make necessary the use of software to manage all data relating to acquisition, characterization, production, storage as well as distribution of biological resources. Currently, none of in-house developed software used by BRCs does not provide all the expected functions and that, for a maximum of types of biological resources. Project Objectives: The purpose of this project, funded by a grant IBiSA GIS, was to develop a generic software, but flexible enough to meet the specific needs of each BRC, ensuring data traceability and compliance with regulations. This software must be distributable under a consortium agreement and interoperable with databases of national and international networks. Ten French microbial BRCs were project partners. In collaboration with the Biology IT Centre of the Institut Pasteur. Topics / materials and methods: The application development was carried out by a service company in collaboration with BRC partners and the Biology IT Centre. The solution developed was composed of a public Web application (FBRCMi-catalog) and a private BRCLIMS application. A BRC partners data recovery was also part of the specification. The development was realized with the Java EE technologies (for the application part) and PostgreSQL 9 (for the database part). The dialogue between BRC-LIMS for each BRC and FBRCMi-catalog, is done via a RESTfull webservice. The maintenance and the new developments are now supported by the Biology IT Centre. Main results: At the end of the project (start of production in January 2013), the BRCs had a custom-designed tool for the management of microbial strains (BRC-LIMS), and a Web application FBRCMi-catalog (accessible via www.fbrcmi.fr) acting as common catalog for all BRCs participating in the project. These tools allow both the internal management of biological resources, their external visibility, and export data to other sites. Conclusions: In conclusion, BRC-LIMS aims to be a tool used daily by BRCs to support users in their tasks and processes, sometimes complex for the management of biological resources. These software applications, allowing data exchange, facilitate the establishment of a national network of BRC microorganisms and potentially others biological resource networks in the future. It was designed to be generic, portable, interoperable and user-friendly as well as awareness of biodiversity represented in the BRCs to the scientific and industrial communities. H03: Eero Lihavainen, Mikhail Kislin, Leonard Khirug and Andre Ribeiro. Automatic quantification of mitochondrial fragmentation from two-photon microscope images of mouse brain tissue Abstract: Mitochondria are organelles that perform various vital functions in cells. Their dysfunctions are observed in many diseases, in particular neurodegenerative ones. Their morphology is shaped via the processes of fusion and fission; as a result, mitochondria can exhibit elongated, networked and fragmented morphologies. Recent research has shown that the fusion-fission dynamics, and consequently the morphology of mitochondria, is intricately related to their functioning; in particular, excess fragmentation of the mitochondrial network is associated with many diseases. Using recently introduced techniques of intravital fluorescence microscope imaging, it is possible to observe mitochondria in tissues of live animals. Combining such methods with animal models of diseases is likely to result in a better understanding of mitochondrial dynamics in disease. However, to exploit the images generated by such studies, novel computational tools are required. Mitochondria are organelles that perform various vital functions in cells. Their dysfunctions are observed in many diseases, in particular neurodegenerative ones. Their morphology is shaped via the processes of fusion and fission; as a result, mitochondria can exhibit elongated, networked and fragmented morphologies. Recent research has shown that the fusion-fission dynamics, and consequently the morphology of mitochondria, is intricately related to their functioning; in particular, excess fragmentation of the mitochondrial network is associated with many diseases. Using recently introduced techniques of intravital fluorescence microscope imaging, it is possible to observe mitochondria in tissues of live animals. Combining such methods with animal models of diseases is likely to result in a better understanding of mitochondrial dynamics in disease. However, to exploit the images generated by such studies, novel computational tools are required. Here, we present a method for the automatic quantification of mitochondrial fragmentation from two-photon fluorescence microscope images of mouse brain tissue, where mitochondria have been fluorescently labeled. The method learns a statistical model to predict a "fragmentation score", based on training data scored by experts, from features computed from a local region of a tissue image. We validate the method, and demonstrate its applicability with quantification results from experiments where mice underwent cardiac arrest. H04: Melissa Mary and Gansel Xavier. LOINC & SNOMED-CT: usability and challenges to code identification tests and results for automated in vitro diagnostics systems Abstract: In many countries simultaneous and similar analysis drove to the implementation of Electronic Medical Record (local to an hospital) and Electronic Health Record (national level) to store patient medical data such as patient allergy, clinical report and in vitro In many countries simultaneous and similar analysis drove to the implementation of Electronic Medical Record (local to an hospital) and Electronic Health Record (national level) to store patient medical data such as patient allergy, clinical report and in vitro