Carbon Nanotubes: Synthesis, Properties and Applications

Recent discoveries of salient carbon nanoforms have paved tremendous interest among research and also toward their discrete applications in scientific fields. Various generation methods for carbon nanotubes (CNTs) involve chemical deposition of vapor, discharge using electric arc and laser ablation mechanism which were driven by functionalization, chemical addition, doping, and filing such that in-depth characterization and manipulation of CNTs were possible. The in-built elasticity, electromechanical, chemical, and optical properties of CNTs have a notable impact on its stability and reactivity. Perhaps, the flexibility along with its determined strength makes them to validate its potential application in diverse fields which enables that these CNTs will definitely procure a prominent role in nanotechnology

Towards efficient data integration and knowledge management in the Agronomic domain

International audienceToday, the revolution in empirical technologies has generated vast amounts of data. This data deluge has created an urgent need to assimilate it with a panoramic view. To this end, information systems play a central role in managing and integrating these data, aiding the biologists in exploiting this integrated information for the extraction of new knowledge. The plant bioinformatics node of the Institut Français de Bioinformatique (IFB) maintains public information systems where a variety of domain specific data are integrated. Currently, efforts are being taken to expose the IFB plant bioinformatics resources as RDF, utilising domain specific ontologies and metadata. Here, we present the overview and the progress of the project

The Agronomic Linked Data (AgroLD) Project. [P0322]

The drastic growth in data in the recent years, within the Agronomic sciences has brought the concept of knowledge management to the forefront. Some of the factors that contribute to this change include a) conducting high-throughput experiments have become affordable, the time spent in generating data through these experiments are minuscule when compared to its integration and analysis; b) publishing data over the web is fairly trivial and c) multiple databases exist for each type of data (i.e. 'omics' data) with a possible overlap or slight variation in its coverage. In most cases these sources remain autonomous and disconnected. Hence, efficiently managed data and the underlying knowledge in principle will make data analysis straightforward aiding in more efficient decision making. At the Institute of Computational Biology (IBC), we are involved in developing methods to aid data integration and knowledge management within the domain of Agronomic sciences to improve information accessibility and interoperability. To this end, we address the challenge by pursuing several complementary research directions towards: distributed, heterogeneous data integration. This talk will focus mainly on,Agronomic Linked Data (AgroLD) wich is a Semantic Web knowledge base designed to integrate data from various publically available plant centric data sources. These include Gramene, Oryzabase, TAIR and resources from the South Green platform among many others. The aim of AgroLD project is to provide a portal for bioinformaticians and domain experts to exploit the homogenized data towards enabling to bridge the knowledge. (Texte integral

The conserved Fanconi anemia nuclease Fan1 and the SUMO E3 ligase Pli1 act in two novel Pso2-independent pathways of DNA interstrand crosslink repair in yeast

DNA interstrand cross-links (ICLs) represent a physical barrier to the progression of cellular machinery involved in DNA metabolism. Thus, this type of adduct represents a serious threat to genomic stability and as such, several DNA repair pathways have evolved in both higher and lower eukaryotes to identify this type of damage and restore the integrity of the genetic material. Human cells possess a specialized ICL-repair system, the Fanconi anemia (FA) pathway. Conversely yeasts rely on the concerted action of several DNA repair systems. Recent work in higher eukaryotes identified and characterized a novel conserved FA component, FAN1 (Fanconi anemia-associated nuclease 1, or FANCD2/FANCI-associated nuclease 1). In this study, we characterize Fan1 in the yeast Schizosaccharomyces pombe. Using standard genetics, we demonstrate that Fan1 is a key component of a previously unidentified ICL-resolution pathway. Using high-throughput synthetic genetic arrays, we also demonstrate the existence of a third pathway of ICL repair, dependent on the SUMO E3 ligase Pli1. Finally, using sequence-threaded homology models, we predict and validate key residues essential for Fan1 activity in ICL repair

Finding gene regulatory network candidates using the gene expression knowledge base

BACKGROUND: Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of ‘omics’ data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. RESULTS: We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. CONCLUSIONS: Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-014-0386-y) contains supplementary material, which is available to authorized users

Application of Semantic Web Technology to Establish Knowledge Management and Discovery in the Life Sciences

The last three decades has seen the successful development of many high-throughput technologies that have revolutionised and transformed biological research. The application of these technologies has generated large quantities of data allowing new approaches to analyze and integrate these data, which now constitute the field of Systems Biology. Systems Biology aims to enable a holistic understanding of a biological system by mapping interactions between all the biochemical components within the system. This requires integration of interdisciplinary data and knowledge to comprehensively explore the various biological processes of a system. Ontologies in biology (bio-ontologies) and the Semantic Web are playing an increasingly important role in the integration of data and knowledge by offering an explicit, unambiguous and rich representation mechanism. This increased influence led to the proposal of the Semantic Systems Biology paradigm to complement the techniques currently used in Systems Biology. Semantic Systems Biology provides a semantic description of the knowledge about the biological systems on the whole facilitating data integration, knowledge management, reasoning and querying. However, this approach is still a typical product of technology push, offering potential users access to the new technology. This doctoral thesis presents the work performed to bring Semantic Systems Biology closer to biological domain experts. The work covers a variety of aspects of Semantic Systems Biology: The Gene eXpression Knowledge Base is a resource that captures knowledge on gene expression. The knowledge base exploits the power of seamless data integration offered by the semantic web technologies to build large networks of varied datasets, capable of answering complex biological questions. The knowledge base is the result of the active collaboration with the Gastrin Systems Biology group here at the Norwegian University of Science and Technology. This resource was customised by the integration of additional data sets on users’ request. Additionally, the utility of the knowledge base is demonstrated by the conversion of biological questions into computable queries. The joint analysis of the query results has helped in filling knowledge gaps in the biological system of study. Biologists often use different bioinformatics tools to conduct complex biological analysis. However, using these tools frequently poses a steep learning curve for the life science researchers. Therefore, the thesis describes ONTO-ToolKit, a plug-in that allows biologists to exploit bio-ontology based analysis as part of biological workflows in Galaxy. ONTO-ToolKit allows users to perform ontology-based analysis to improve the depth of their overall analysis Visualisation plays a key role in aiding users understand and grasp the knowledge represented in bio-ontologies. To this end, OLSVis, a web application was developed to make ontology browsing intuitive and flexible. Finally, the steps needed to further advance the Semantic Systems Biology approach has been discussed.Semantic Systems Biolog

OLSVis: an animated, interactive visual browser for bio-ontologies

Background: More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible. Results: We created the OLSVis web application, a visualiser for browsing all ontologies available in the OLS database. OLSVis shows customisable subgraphs of the OLS ontologies. Subgraphs are animated via a real-time force-based layout algorithm which is fully interactive: each time the user makes a change, e.g. browsing to a new term, hiding, adding, or dragging terms, the algorithm performs smooth and only essential reorganisations of the graph. This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph. URL: http://ols.wordvis.com Conclusions: The OLSVis web application provides a user-friendly tool to visualise ontologies from the OLS repository. It broadens the possibilities to investigate and select ontology subgraphs through a smooth visualisation method. Keywords: Bio-ontologies, Visualisation, Browsing, Web applicatio