Da ciência à e-ciência: paradigmas da descoberta do conhecimento

Gradualmente, a computação está deixando de ser apenas uma “ferramenta de apoio” a novas pesquisas para se tornar parte fundamental das ciências com que interage e de seus métodos científicos. A sinergia entre ciência da computação e as outras áreas do conhecimento criou um novo modo de se fazer ciência – a e-science (ou e-ciência) – que unifica teoria, experimentos e simulação, ao mesmo tempo em que lida com uma quantidade enorme de informação. O uso de computação em nuvem tem o potencial de permitir que pesquisas antes restritas àqueles com acesso a supercomputadores possam ser realizadas por qualquer pesquisador. Este artigo apresenta uma breve descrição da evolução dos paradigmas do modo de se fazer ciência (do empirismo ao panorama atual da e-science) e aborda o potencial da computação em nuvem como ferramenta catalisadora de pesquisa transformativa.Computer Science is gradually evolving from a mere “supporting tool” for research in other fields and turning into an intrinsic part of the very methods of the sciences with which it interacts. The synergy between Computer Science and other fields of knowledge created a novel way of doing science – called eScience – which unifies theory, experiments, and simulations, enabling researchers to deal with huge amounts of information. The use of cloud computing has the potential to allow any researcher to conduct works previously restricted to those with access to supercomputers. This article presents a brief history of the evolution of scientific paradigms (from empiricism to the current landscape of eScience) and discusses the potential of cloud computing as a tool capable of catalyzing transformative research

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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p