Model-Based Engineering Applied to the Interpretation of the Human Genome

Pastor, Óscar; Levin, Ana M.; Celma, Matilde; Casamayor, Juan Carlos; Virrueta, Aremy; Eraso, Luis E.

doi:10.1007/978-3-642-17505-3_14

Cited by 11 publications

(12 citation statements)

References 6 publications

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“…The option of dealing with various types of species is also considered. The methodological approach followed in the design and 4 Universitat Politècnica de València development of the system, allows the easy integration of new views of the genome domain and the load of new data sources.…”

Section: Discussionmentioning

confidence: 99%

“…Chromosome class, which is the main class of the overall complete conceptual model [4]. In addition, the Variation class is also related to the Databank class, which represents the source where the variation has been found, the attribute id_variation_db specifies the name of the variation in the corresponding database source.…”

Section: Conceptual Model Definitionmentioning

confidence: 99%

“…As a result, the description and categorization of variations is unified. This model is a view of a broader model [4] that conceptualizes the whole genome domain and it is being developed currently. Once this variation conceptual model is established, it is implemented in a database (Human Genome DataBase, HGDB).…”

Section: Introductionmentioning

confidence: 99%

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Integrating Human Genome Variation Data: An Information System Approach

Martin

Celma

2011

2011 22nd International Workshop on Database and Expert Systems Applications

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The goal of this work is to design and develop an Information System that integrates human genome variation data currently scattered in different repositories. The continuous and increasing interest generated around the variations knowledge, makes the study of this research topic from an Information System point of view extremely attractive.The system has been developed following a conceptual-model based methodology. The conceptual model represents, in a formal way, genome variation knowledge. The definition and categorization of variations is unified using this conceptualization. Once this conceptual model is established, it is implemented in a database (Human Genome DataBase, HGDB). The database acts as a unified variation repository of integrated information that will allow biologists to perform efficient recovery tasks. Lastly, a loading module has been implemented, using an extraction-transformation-load (ETL) strategy, in order to integrate data from three relevant variation repositories: HapMap, Ensembl and Cosmic. An exploitation module for final users is also provided.

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Section: Discussionmentioning

confidence: 99%

Section: Conceptual Model Definitionmentioning

confidence: 99%

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Integrating Human Genome Variation Data: An Information System Approach

Martin

Celma

2011

2011 22nd International Workshop on Database and Expert Systems Applications

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“…Diagen is classied as a model-driven framework because each of its components (classes, data entities, operations) is a projection of the Conceptual Schema of the Human Genome (CSHG) [10]. The CSGH is a conceptual model created with the collaboration of geneticists, where biological concepts related to the human genome have been precisely addressed and dened.…”

Section: An Integrative Framework For Bioinformaticsmentioning

confidence: 99%

“…The rst mechanism obtains some data from the ENSEMBL database [15]. The second mechanism retrieves genetic information from the HGBD database [16] based on the Conceptual Schema of the Human Genome (CSHG) [10].…”

Section: An Integrative Framework For Bioinformaticsmentioning

confidence: 99%

Diagen: A Model-Driven Framework for Integrating Bioinformatic Tools

Villanueva

Valverde

Levin

et al. 2012

Lecture Notes in Business Information Processing

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Abstract. Nowadays, the diagnosis of disease based on genomic information is feasible by searching genetic variations on DNA sequences. However, geneticists struggle with bioinformatic tools that are supposed to simplify DNA sequence analysis. As a universal tool to support every requirement is far from be implemented, geneticists themselves must solve the data exchange among several tools. Due to the fact that there are no standards to support this integration task, it must be managed in every analysis. This paper proposes addressing this integration by means of a model-driven framework. The Diagen framework is a software implementation based on conceptual modeling principles that formalizes data exchange and simplies bioinformatic tool integration. First, we analyze how conceptual modeling can be used to deal with data exchange among tools. And then, as a proof of concept, the presented framework is used to search for variations on the BRCA2 gene using real DNA samples and a set of specic bioinformatic tools.

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A Comprehensive Approach for the Conceptual Modeling of Genomic Data

Bernasconi

Ceri

et al. 2022

Conceptual Modeling

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The human genome is traditionally represented as a DNA sequence of three billion base pairs. However, its intricacies are captured by many more complex signals, representing DNA variations, the expression of gene activity, or DNA's structural rearrangements; a rich set of data formats is used to represent such signals. Different conceptual models explain such elaborate structure and behavior. Among them, the Conceptual Schema of the Human Genome (CSG) provides a concept-oriented, top-down representation of the genome behaviorindependent of data formats. The Genomic Conceptual Model (GCM) instead provides a data-oriented, bottom-up representation, targeting a well-organized, unified description of these formats. We hereby propose to join these two approaches to achieve a more complete vision, linking (1) a concepts layer, describing genome elements and their conceptual connections, with (2) a data layer, describing datasets derived from genome sequencing with specific technologies. The link is established when specific genomic data types are chosen in the data layer, thereby triggering the selection of a view in the concepts layer. The benefit is mutual, as data records can be semantically described by high-level concepts and exploit their links. In turn, the continuously evolving abstract model can be extended thanks to the input provided by real datasets. As a result, it will be possible to express queries that employ a holistic conceptual perspective on the genome, directly translated onto data-oriented terms and organization. The approach is here exemplified using the DNA variation data type but is applicable to all genomic information.

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Model-Based Engineering Applied to the Interpretation of the Human Genome

Cited by 11 publications

References 6 publications

Integrating Human Genome Variation Data: An Information System Approach

Integrating Human Genome Variation Data: An Information System Approach

Diagen: A Model-Driven Framework for Integrating Bioinformatic Tools

A Comprehensive Approach for the Conceptual Modeling of Genomic Data

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