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A visualization interface for spatial pathway regulation data
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Data visualization is an essential methodology for bioinformatics studies. Spatial Transcriptomics(ST) is a method that aims at measuring the transcriptome of tissue sections while maintaining its spacial information. Finally, the study of biological pathway focuses on a series of biochemical reactions that take place in organisms. As these studies generate a large number of datasets, this thesis attempts to combine the ST’s data with pathwayinformation and visualize it in an intuitive way to assist user comprehension and insight.In this thesis, Python was used for integrating the dataset and JavaScript libraries wereused for building the visualization. The processing of ST pathway data together with the data visualization interface are the outcomes of this thesis. The data visualization can show the regulation of pathways in the ST data and can be accessed by modern browsers. These outcomes can help users navigate the ST and pathway datasets more effectively.

Abstract [sv]

Datavisualisering är en viktig del av bioinformatik. Spatial transkriptomik (ST) är en metod som mäter transkriptom, samtidigt som den behåller spatial information. Biologiskapathways å andrasidan fokuserar på biokemiska reaktioner som sker inom organismer. Dessa studier genererar mycket data, och denna avhandling försöker att kombinera ST-data med pathway information och få en intuitiv visualisering av det integrerade datat.I avhandlingen användes Python för att integrera datat och JavaScript bibliotek för attbygga visualiseringsverktyget. Avhandlingen resulterade i en metod för att integrera STdata och pathway information, samt ett visualiseringsverktyg för ovan nämnda information.Verktyget kan visa pathway regulationer i ST data och kan användas i moderna webbläsare.Forskningen resulterade i ett verktyg som kan hjälpa forskare att förstå ST och pathwaydata.

Place, publisher, year, edition, pages
2018. , p. 38
Keywords [en]
Data Visualization, Pathway, Spatial Transcriptomics, JavaScript, Python
National Category
Natural Sciences Chemical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-237741OAI: oai:DiVA.org:kth-237741DiVA, id: diva2:1259563
Available from: 2018-10-30 Created: 2018-10-30 Last updated: 2018-10-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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