A Port Graph Rewriting Approach to Relational Database Modelling

International audienceWe present new algorithms to compute the Syntactic Closure and the Minimal Cover of a set of functional dependencies, using strategic port graph rewriting. We specify a Visual Domain Specific Language to model relational database schemata as port graphs, and provide an extension to port graph rewriting rules. Using these rules we implement strategies to compute a syntactic closure, analyse it and find minimal covers, essential for schema normalisation. The graph program provides a visual description of the computation steps coupled with analysis features not available in other approaches. We prove soundness and completeness of the computed closure. This methodology is implemented in PORGY

Degenerate T-cell Recognition of Peptides on MHC Molecules Creates Large Holes in the T-cell Repertoire

The cellular immune system screens peptides presented by host cells on MHC molecules to assess if the cells are infected. In this study we examined whether the presented peptides contain enough information for a proper self/nonself assessment by comparing the presented human (self) and bacterial or viral (nonself) peptides on a large number of MHC molecules. For all MHC molecules tested, only a small fraction of the presented nonself peptides from 174 species of bacteria and 1000 viral proteomes (0.2%) is shown to be identical to a presented self peptide. Next, we use available data on T-cell receptor-peptide-MHC interactions to estimate how well T-cells distinguish between similar peptides. The recognition of a peptide-MHC by the T-cell receptor is flexible, and as a result, about one-third of the presented nonself peptides is expected to be indistinguishable (by T-cells) from presented self peptides. This suggests that T-cells are expected to remain tolerant for a large fraction of the presented nonself peptides, which provides an explanation for the “holes in the T-cell repertoire” that are found for a large fraction of foreign epitopes. Additionally, this overlap with self increases the need for efficient self tolerance, as many self-similar nonself peptides could initiate an autoimmune response. Degenerate recognition of peptide-MHC-I complexes by T-cells thus creates large and potentially dangerous overlaps between self and nonself

Intron Evolution: Testing Hypotheses of Intron Evolution Using the Phylogenomics of Tetraspanins

BACKGROUND: Although large scale informatics studies on introns can be useful in making broad inferences concerning patterns of intron gain and loss, more specific questions about intron evolution at a finer scale can be addressed using a gene family where structure and function are well known. Genome wide surveys of tetraspanins from a broad array of organisms with fully sequenced genomes are an excellent means to understand specifics of intron evolution. Our approach incorporated several new fully sequenced genomes that cover the major lineages of the animal kingdom as well as plants, protists and fungi. The analysis of exon/intron gene structure in such an evolutionary broad set of genomes allowed us to identify ancestral intron structure in tetraspanins throughout the eukaryotic tree of life. METHODOLOGY/PRINCIPAL FINDINGS: We performed a phylogenomic analysis of the intron/exon structure of the tetraspanin protein family. In addition, to the already characterized tetraspanin introns numbered 1 through 6 found in animals, three additional ancient, phase 0 introns we call 4a, 4b and 4c were found. These three novel introns in combination with the ancestral introns 1 to 6, define three basic tetraspanin gene structures which have been conserved throughout the animal kingdom. Our phylogenomic approach also allows the estimation of the time at which the introns of the 33 human tetraspanin paralogs appeared, which in many cases coincides with the concomitant acquisition of new introns. On the other hand, we observed that new introns (introns other than 1-6, 4a, b and c) were not randomly inserted into the tetraspanin gene structure. The region of tetraspanin genes corresponding to the small extracellular loop (SEL) accounts for only 10.5% of the total sequence length but had 46% of the new animal intron insertions. CONCLUSIONS/SIGNIFICANCE: Our results indicate that tests of intron evolution are strengthened by the phylogenomic approach with specific gene families like tetraspanins. These tests add to our understanding of genomic innovation coupled to major evolutionary divergence events, functional constraints and the timing of the appearance of evolutionary novelty

A genomic analysis of the archaeal system Ignicoccus hospitalis-Nanoarchaeum equitans

Sequencing of the complete genome of Ignicoccus hospitalis gives insight into its association with another species of Archaea, Nanoarchaeum equitans

Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case

[EN] Data Warehousing applied in Big Data contexts has been an emergent topic of research, as traditional Data Warehousing technologies are unable to deal with Big Data characteristics and challenges. The methods used in this field are already well systematized and adopted by practitioners, while research in Big Data Warehousing is only starting to provide some guidance on how to model such complex systems. This work contributes to the process of designing conceptual data models for Big Data Warehouses proposing a method based on rules and design patterns, which aims to gather the information of a certain application domain mapped in a relational conceptual model. A complex domain that can benefit from this work is Genomics, characterized by an increasing heterogeneity, both in terms of content and data structure. Moreover, the challenges for collecting and analyzing genome data under a unified perspective have become a bottleneck for the scientific community, reason why standardized analytical repositories such as a Big Genome Warehouse can be of high value to the community. In the demonstration case presented here, a genomics relational model is merged with the proposed Big Data Warehouse Conceptual Metamodel to obtain the Big Genome Warehouse Conceptual Model, showing that the design rules and patterns can be applied having a relational conceptual model as starting point.This work has been supported by FCT - Fundação para a Ciên-cia e Tecnologia within the Project Scope: UID/CEC/00319/2019, the Doctoral scholarship PD/BDE/135100/2017 and European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039479; Funding Reference: POCI-01-0247-FEDER-039479]. We also thank both the Spanish State Research Agency and the Generalitat Valenciana under the projects DataME TIN2016-80811-P, ACIF/2018/171, and PROMETEO/2018/176. Icons made by Freepik, from www.flaticon.com.Galvão, J.; León-Palacio, A.; Costa, C.; Santos, MY.; Pastor López, O. (2020). Towards Designing Conceptual Data Models for Big Data Warehouses: The Genomics Case. Springer Nature. 3-19. https://doi.org/10.1007/978-3-030-63396-7_1S319Krishnan, K.: Data Warehousing in the Age of Big Data. Morgan Kaufmann is an imprint of Elsevier, Amsterdam (2013)Santos, M.Y., Costa, C.: Big Data: Concepts, Warehousing and Analytics. River Publishers, Aalborg (2020)Cuzzocrea, A., Moussa, R.: Multidimensional database modeling: literature survey and research agenda in the big data era. In: 2017 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1–6 (2017)Di Tria, F., Lefons, E., Tangorra, F.: Design process for big data warehouses. In: 2014 International Conference on Data Science and Advanced Analytics (DSAA), pp. 512–518. IEEE (2014)Dehdouh, K., Bentayeb, F., Boussaid, O., Kabachi, N.: Using the column oriented NoSQL model for implementing big data warehouses. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA) (2015)Bézivin, J.: On the unification power of models. Softw. Syst. Model. 4(2), 171–188 (2005). https://doi.org/10.1007/s10270-005-0079-0Reyes Román, J.F., Pastor, Ó., Casamayor, J.C., Valverde, F.: Applying conceptual modeling to better understand the human genome. In: Comyn-Wattiau, I., Tanaka, K., Song, I.-Y., Yamamoto, S., Saeki, M. (eds.) ER 2016. LNCS, vol. 9974, pp. 404–412. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46397-1_31Embley, D.W., Liddle, S.W.: Big data—conceptual modeling to the rescue. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 1–8. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41924-9_1Giebler, C., Gröger, C., Hoos, E., Schwarz, H., Mitschang, B.: Modeling data lakes with data vault: practical experiences, assessment, and lessons learned. In: Laender, A.H.F., Pernici, B., Lim, E.-P., de Oliveira, J.P.M. (eds.) ER 2019. LNCS, vol. 11788, pp. 63–77. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33223-5_7Gil, D., Song, I.-Y.: Modeling and management of big data: challenges and opportunities. Future Gener. Comput. Syst. 63, 96–99 (2016)Di Tria, F., Lefons, E., Tangorra, F.: GrHyMM: a graph-oriented hybrid multidimensional model. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) ER 2011. LNCS, vol. 6999, pp. 86–97. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24574-9_12Santos, M.Y., Costa, C.: Data warehousing in big data: from multidimensional to tabular data models. In: Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering, pp. 51–60. ACM, New York (2016)Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Wiley, Hoboken (2013)Costa, C., Santos, M.Y.: Evaluating several design patterns and trends in big data warehousing systems. In: Krogstie, J., Reijers, H.A. (eds.) CAiSE 2018. LNCS, vol. 10816, pp. 459–473. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91563-0_28Santos, M.Y., Costa, C., Galvão, J., Andrade, C., Pastor, O., Marcén, A.C.: Big data warehousing for efficient, integrated and advanced analytics - visionary paper. In: Cappiello, C., Ruiz, M. (eds.) CAiSE 2019. LNBIP, vol. 350, pp. 215–226. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21297-1_1

Revealing the Conceptual Schemas of RDF Datasets

International audienceRDF-based datasets, thanks to their semantic richness, variety and fine granularity, are increasingly used by both researchers and business communities. However, these datasets suffer a lack of completeness as the content evolves continuously and data contributors are loosely constrained by the vocabularies and schemes related to the data sources. Conceptual schemas have long been recognized as a key mechanism for understanding and dealing with complex real-world systems. In the context of the Web of Data and user-generated content, the conceptual schema is implicit. In fact, each data contributor has an implicit personal model that is not known by the other contributors. Consequently, revealing a meaningful conceptual schema is a challenging task that should take into account the data and the intended usage. In this paper, we propose a completeness-based approach for revealing conceptual schemas of RDF data. We combine quality evaluation and data mining approaches to find a conceptual schema for a dataset, this model meets user expectations regarding data completeness constraints. To achieve that, we propose LOD-CM; a web-based completeness demonstrator for linked datasets