CASyM winter school of Systems Medicine took place between March 29th and April 1st 2017 in Ljubljana, Slovenia and is entitled »The 3rd SysBioMed hands-on tutorial: Systems Medicine Approaches in Personalized Medicine«
1Faculty of Information and Computer Science, Ljubljana, Slovenia,2Faculty of Chemistry and Chemical Technology, Ljubljana, Slovenia,3Faculty of Medicine, Ljubljana, Slovenia,4Osir, Ljubljana, Slovenia
Introduction: A vast number of animal samples, such as blood samples and tissues, is collected in research laboratories every day. Samples collected from an animals can be aliquoted and further processed (e.g. DNA or RNA can be isolated). In this way many samples from a single subject are obtained and consequently, an even greater amount of data is gathered. Managing, tracking and analysis of all the samples and the data have become a big issue within the laboratory research environments. Because of the poor and non-systematic organization data can get lost and the samples are no longer tracked. Therefore, a need for an information system, which would help to manage the collected samples and data, appeared.
Results: We present a design and implementation of an information system, which supports various tasks. It is able to (1) serve as a database of the collected, analysed and stored samples, (2) manage the registered data and (3) prepare the acquired data to be computationally analysed. The system is designed for the use in the field of laboratory animals and incorporates several experimental workflows ranging from the initial collection of samples and their aliquots to the subsequent biochemical (or other) analyses. The information system supports data import and export in CSV format, which makes it compatible with the majority of commercial software products for data management and analysis. It is designed with open-source tools and platforms. It is easy to maintain and can be customized according to the users’ demands.
Conclusion: The information system helps to organize the collected animal samples and data. It does it in a way that is adequate also for laboratories where a large number of samples is collected. Open-source tools and platforms make the system accessible to a wide scientific community. Additionally, its simplicity and flexibility make it even more user friendly. We strongly believe that the proposed system presents an excellent alternative to the popular general-purpose computational tools that are currently prevalent within research laboratories.
Acknowledgements: This work was co-financed by the Republic of Slovenia and the European Union under the European Social Fund (25-13-3), by Slovenian Research Agency grants P1-0390, P2-0359 and the infrastructure grant ELIXIR.
2006 - University of Ljubljana, Faculty of Medicine, Center for Functional Genomics and Bio-chips.