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Optimization of quality assured dataflow from biosensors: Time series analysis of plankton respiration by oxygen optode
Umeå University, Faculty of Science and Technology, Umeå Marine Sciences Centre (UMF). Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. Umeå University, Faculty of Science and Technology, Department of Computing Science. (Johan Wikner)
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Data analysis can be a time consuming part of an experimental method, especially when the method is used frequently and large amounts of data are produced each time. In this study, an application software was developed to improve work flow and data management for respiration rate measurements using an optical oxygen sensor. The application was used to analyze data files from the oxygen sensor without the need to manually enter and analyze the data in a spreadsheet application. The software was written in the Python programming language and utilized available scientific computing packages as well as a graphical user interface framework to provide user friendly access to all functions. Any number of files with experimental data were imported into the program and a linear regression analysis was done for each file and viewed to verify the quality of the data. Tables and summarizing graphs were used to display the key information and statistical results. The final results were exported for use in other applications. Data processing that used to take an hour to complete was done with the new application in five to ten minutes and the risk of introducing human errors in the data was simultaneously reduced. User tests indicated that learning the basics of the program was easy. This study shows the usefulness of a bioinformatics approach and the tools provided by Python and its related software to solve problems that arise with managing large volumes of numerical data.

Place, publisher, year, edition, pages
2015. , p. 17
Keywords [en]
sensor, oxygen, data, compilation, quality assurance, calculations, flow
Keywords [sv]
sensor, syre, data, behandling, kvalitetsäkring, beräkning, flöde
National Category
Diagnostic Biotechnology
Identifiers
URN: urn:nbn:se:umu:diva-151502OAI: oai:DiVA.org:umu-151502DiVA, id: diva2:1245768
Educational program
Master of Science Programme in Biotechnology
Supervisors
Projects
Älvburet organiskt kol och bakteriers syre respirationAvailable from: 2019-05-07 Created: 2018-09-06 Last updated: 2019-05-07Bibliographically approved

Open Access in DiVA

Lindmark2015SensorDataFlow(702 kB)16 downloads
File information
File name FULLTEXT01.pdfFile size 702 kBChecksum SHA-512
a5a258e3fb8b05115f9b4ce217b15aba0f303a68466bc9b6b3e63764ef33a6a7c2c8e7afe6dc7a73db876b2358fe80e27b78ead7fb65a5f9433c88bf8bd01092
Type fulltextMimetype application/pdf

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Umeå Marine Sciences Centre (UMF)Department of Ecology and Environmental SciencesDepartment of Computing Science
Diagnostic Biotechnology

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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Output format
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