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2011MASI01.pdf2.55 MBAdobe PDFView/Open
Authors: Thi Cam Thach, Doan
Department: Högskolan i Borås/Institutionen Handels- och IT-högskolan
Issue Date: 19-Oct-2011
Series/Report no.: Masteruppsats
Programme: Masterutbildning i Informatik
Publisher: University of Borås/School of Business and IT
Media type: text
Keywords: human computer interaction
information visualization
interactive user interface
Abstract: Recently, the whole-genome expression analysis – which is analyzing most or all of the genes in biological systems, and is a rich and powerful way to discover gene pathway - has become increasingly affordable because of the increasing amount of microarray data available in public databases. Additionally, due to the enormously available information content in these repositories, researchers have to spend large amount of time to decide on the right information to proceed. There should be an application to assist biological researchers reducing the time in finding good data sets to analyze. In this project, a thorough study in HCI, Information Visualization, interaction design and development methodologies are carried out in order to build a web-based user interface that enables searching and browsing gene expression data and their correlation (web-based). Findings from literature review are applied to create a web-based user interface in large-gene expression analysis. Then, a survey is carried out to collect and analyze pilot users‟ feedback. The questionnaire shows that the users are very interested in using the system and they would like to spend more time interacting with it. They give positive feedbacks about interactive data visualization in the website help them to save time on viewing, navigating and interpreting complicated data. Besides, it is easy to navigate and learn how to use the system to achieve interesting findings in biology. The questionnaire shows that the author is successful in applying findings from literature review to build the website. Besides, from the results there are suggestions for improvement such as the flexibility in the website by automatically recognizing the alias gene names from different databases, filling-in gene symbols using first few characters, narrowing down a search to a particular species such as human or rat, etc.
Appears in Collections:Masteruppsatser (Informatics)

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