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      A rigorous approach to facilitate and guarantee the correctness of the genetic testing management in human genome information systems

      research-article
      1 , , 2 , 3 , 4 , 4 , 2 , 3 ,
      BMC Genomics
      BioMed Central
      6th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-meeting 2010)
      15-18 November 2010

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          Abstract

          Background

          Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes.

          Results

          This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra.

          Conclusions

          This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.

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          Most cited references21

          • Record: found
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          • Article: not found

          BioAmbients: an abstraction for biological compartments

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            • Record: found
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            Using Petri Net tools to study properties and dynamics of biological systems.

            Petri Nets (PNs) and their extensions are promising methods for modeling and simulating biological systems. We surveyed PN formalisms and tools and compared them based on their mathematical capabilities as well as by their appropriateness to represent typical biological processes. We measured the ability of these tools to model specific features of biological systems and answer a set of biological questions that we defined. We found that different tools are required to provide all capabilities that we assessed. We created software to translate a generic PN model into most of the formalisms and tools discussed. We have also made available three models and suggest that a library of such models would catalyze progress in qualitative modeling via PNs. Development and wide adoption of common formats would enable researchers to share models and use different tools to analyze them without the need to convert to proprietary formats.
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              An ontology for biological function based on molecular interactions.

              P Karp (2000)
              A number of important bioinformatics computations involve computing with function: executing computational operations whose inputs or outputs are descriptions of the functions of biomolecules. Examples include performing functional queries to sequence and pathway databases, and determining functional equality to evaluate algorithms that predict function from sequence. A prerequisite to computing with function is the existence of an ontology that provides a structured semantic encoding of function. Functional bioinformatics is an emerging subfield of bioinformatics that is concerned with developing ontologies and algorithms for computing with biological function. The article explores the notion of computing with function, and explains the importance of ontologies of function to bioinformatics. The functional ontology developed for the EcoCyc database is presented. This ontology can encode a diverse array of biochemical processes, including enzymatic reactions involving small-molecule substrates and macromolecular substrates, signal-transduction processes, transport events, and mechanisms of regulation of gene expression. The ontology is validated through its use to express complex functional queries for the EcoCyc DB. pkarp@ai.sri.com
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                Author and article information

                Conference
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2011
                22 December 2011
                : 12
                : Suppl 4
                : S13
                Affiliations
                [1 ]EACH - School of Arts, Sciences and Humanities, University of São Paulo, Rua Arlindo Béttio, 1000, Ermelino Matarazzo, São Paulo, Brazil
                [2 ]CERCS, Georgia Institute of Technology, 266 First Drive, Atlanta, GA 30332-0765, USA
                [3 ]Institute of Mathematics and Statistics, Computer Science Department, University of São Paulo, Rua do Matão, 1010, 05508-900, São Paulo, SP, Brazil
                [4 ]The Human Genome Research Center, University of São Paulo, Rua do Matão, Travessa 13,106, 05508-900, São Paulo, SP, Brazil
                Article
                1471-2164-12-S4-S13
                10.1186/1471-2164-12-S4-S13
                3287582
                22369688
                d17b811e-3044-46d7-afea-e6ae5ae6424d
                Copyright ©2011 Araújo et al; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                6th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-meeting 2010)
                Ouro Preto, Brazil
                15-18 November 2010
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                Genetics
                Genetics

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