This article is part of the supplement: Proceedings of the 6th International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-meeting 2010)

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

Luciano V Araújo1*, Simon Malkowski2, Kelly R Braghetto3, Maria R Passos-Bueno4, Mayana Zatz4, Calton Pu2 and João E Ferreira3*

Author 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

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BMC Genomics 2011, 12(Suppl 4):S13  doi:10.1186/1471-2164-12-S4-S13

Published: 22 December 2011



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.


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.


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.