11 research outputs found

    The eDAL Suite: Tools and Concepts for Primary Data Citation

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    Retrieval and citation of primary data is the important factor in the approaching age of “data science”. Digital data are easily shared, and just as easily wiped or lost. The problem of keeping on-line data accessible and
retrievable is especially difficult for SME like plant breeders plant biotech companies as well as research projects in this domain.
Intension of eDAL is the provisioning of an information retrieval and data citation infrastructure that meets the requirements of the “data science” age and implements a re-usable platform for data retrieval, data
citation, and data publication. Like a shopping cart, the idea is to combine a search engine and a data cart, which retrieves, rank and collect query relevant data from crop plant data centers

    The LAILAPS Search Engine: A Feature Model for Relevance Ranking in Life Science Databases

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    Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.d

    Quantitative multilevel analysis of central metabolism in developing oilseeds of oilseed rape during in vitro culture

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    Seeds provide the basis for many food, feed, and fuel products. Continued increases in seed yield, composition, and quality require an improved understanding of how the developing seed converts carbon and nitrogen supplies into storage. Current knowledge of this process is often based on the premise that transcriptional regulation directly translates via enzyme concentration into flux. In an attempt to highlight metabolic control, we explore genotypic differences in carbon partitioning for in vitro cultured developing embryos of oilseed rape (Brassica napus). We determined biomass composition as well as 79 net fluxes, the levels of 77 metabolites, and 26 enzyme activities with specific focus on central metabolism in nine selected germplasm accessions. Overall, we observed a tradeoff between the biomass component fractions of lipid and starch. With increasing lipid content over the spectrum of genotypes, plastidic fatty acid synthesis and glycolytic flux increased concomitantly, while glycolytic intermediates decreased. The lipid/starch tradeoff was not reflected at the proteome level, pointing to the significance of (posttranslational) metabolic control. Enzyme activity/flux and metabolite/flux correlations suggest that plastidic pyruvate kinase exerts flux control and that the lipid/starch tradeoff is most likely mediated by allosteric feedback regulation of phosphofructokinase and ADP-glucose pyrophosphorylase. Quantitative data were also used to calculate in vivo mass action ratios, reaction equilibria, and metabolite turnover times. Compounds like cyclic 39,59-AMP and sucrose-6-phosphate were identified to potentially be involved in so far unknown mechanisms of metabolic control. This study provides a rich source of quantitative data for those studying central metabolism

    BioNetLink - An Architecture for Working with Network Data

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    The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks

    The LAILAPS Search Engine: A Feature Model for Relevance Ranking in Life Science Databases

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    Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking

    The LAILAPS Search Engine: Relevance Ranking in Life Science Databases

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    Search engines and retrieval systems are popular tools at a life science desktop. The manual inspection of hundreds of database entries, that reflect a life science concept or fact, is a time intensive daily work. Hereby, not the number of query results matters, but the relevance does. In this paper, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases

    Visual Exploration of Large Metabolic Models

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    Motivation:Large metabolic models, including genome-scale metabolic models (GSMMs), are nowadays common in systems biology, biotechnology and pharmacology. They typically contain thousands of metabolites and reactions and therefore methods for their automatic visualisation and interactive exploration can facilitate a better understanding of these models.Results:We developed a novel method for the visual exploration of large metabolic models and implemented it in LMME (Large Metabolic Model Explorer), an add-on for the biological network analysis tool VANTED. The underlying idea of our method is to analyse a large model as follows. Starting from a decomposition into several subsystems, relationships between these subsystems are identified and an overview is computed and visualised. From this overview, detailed subviews may be constructed and visualised in order to explore subsystems and relationships in greater detail. Decompositions may either be predefined or computed, using built-in or self-implemented methods. Realised as add-on for VANTED, LMME is embedded in a domain-specific environment, allowing for further related analysis at any stage during the exploration. We describe the method, provide a use case, and discuss the strengths and weaknesses of different decomposition methods.Availability:The methods and algorithms presented here are implemented in LMME, an open-source add-on for VANTED. LMME can be downloaded from www.cls.uni-konstanz.de/software/lmme and VANTED can be downloaded from www.vanted.org. The source code of LMME is available from GitHub, at https://github.com/LSI-UniKonstanz/lmme.publishe

    Identification of a Disulfide Bridge Essential for Transport Function of the Human Proton-coupled Amino Acid Transporter hPAT1*

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    The proton-coupled amino acid transporter 1 (PAT1, SLC36A1) mediates the uptake of small neutral amino acids at the apical membrane of intestinal epithelial cells after protein digestion. The transporter is currently under intense investigation, because it is a possible vehicle for oral drug delivery. Structural features of the protein such as the number of transmembrane domains, the substrate binding site, or essential amino acids are still unknown. In the present study we use mutagenesis experiments and biochemical approaches to determine the role of the three putative extracellular cysteine residues on transport function and their possible involvement in the formation of a disulfide bridge. As treatment with the reducing reagent dithiothreitol impaired transport function of hPAT1 wild type protein, substitution of putative extracellular cysteine residues Cys-180, Cys-329, and Cys-473 by alanine or serine was performed. Replacement of the two highly conserved cysteine residues Cys-180 and Cys-329 abolished the transport function of hPAT1 in Xenopus laevis oocytes. Studies of wild type and mutant transporters expressed in human retinal pigment epithelial (HRPE) cells suggested that the binding of the substrate was inhibited in these mutants. Substitution of the third putative extracellular nonconserved cysteine residue Cys-473 did not affect transport function. All mutants were expressed at the plasma membrane. Biotinylation of free sulfhydryl groups using maleimide-PEG11-biotin and SDS-PAGE analysis under reducing and nonreducing conditions provided direct evidence for the existence of an essential disulfide bond between Cys-180 and Cys-329. This disulfide bridge is very likely involved in forming or stabilizing the substrate binding site
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