SIGLa: um LIMS baseado em workflows adaptáveis com suporte a múltiplos laboratórios

• Ano de defesa: 2010
• Autor(a) principal: Alexandre Simoes de Melo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Fluxo de trabalho; Bioinformática; Computação
• Link de acesso: http://hdl.handle.net/1843/SLSS-85BKRR

The need to manage large amounts of data is a demand for laboratories. The use of Laboratory Information Management Systems (LIMS) to achieve this is increasing continuously. A LIMS is a complex computational system used to manage laboratory data with emphasis in quality assurance. Several LIMS are available currently. However, most of them have proprietary code and are commercialized at a high cost. Moreover, due to its complexity, LIMS are usually designed to comply with the needs of one kind of laboratory, making it very difficult to reuse a LIMS. In this work we describe the Sistema Integrado de Gerência de Laboratórios (SIGLa), an open source LIMS with a new approach designed to allow it to adapt its activities and processes to various types of laboratories. To accomplish this SIGLa incorporates a workflow management system, making it possible to create and manage customized workflows. For each new laboratory a workflow is defined with its activities, rules and procedures. During the execution, for each workflow created, the values of attributes defined in a XPDL file (which describes the workflow) are stored in SIGLa's database, allowing them to be managed and retrieved upon request. The proteomic laboratory was used as first model for SIGLa development. To check the SIGLa capability of adapting to multiple laboratories, we defined a second workflow modeling a microarray laboratory. This workflow was constructed in a few days illustrating the flexibility and power of the method proposed. With SIGLa's development we hope to contribute positively to the area of management of complex data in laboratory by managing its large amounts of data, guaranteeing the consistence of the data and increasing the laboratory productivity. We also hope to make possible to laboratories with little resources to afford a high level system for complex data management.