{"id":{"repo_id":"abertay","oai_identifier":"oai:rke.abertay.ac.uk:studenttheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad"},"canonical_url":"https://search.dev.ndltd.org/etd/abertay/oai:rke.abertay.ac.uk:studenttheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad","repository":{"repo_id":"abertay","name":"Abertay University","base_url":"https://rke.abertay.ac.uk/ws/oai"},"display":{"title":"Evaluating interactive network visualisations: a case study using the cell Signalling Visualisation Toolkit","abstract":"Cancer is one of the leading causes of death worldwide and arises from cells that do not function properly. Cell functioning is governed in part by signalling pathways within the cell that translate environmental signals detected at the cell membrane into cell behaviour. The dynamic nature and topological complexity of these pathways gives cells the ability to adapt to a wide range of perturbations and can make cells resistant to drug therapy. Systems biology models provide the means to simulate signalling pathways and their dynamics and help scientists gain a better understanding of the inner workings of cells, which informs development of anti-cancer drugs. However, signalling networks’ complexity means that models are challenging to use, and it is difficult to present simulation results effectively. The research work described in this thesis developed a Signalling Visualisation Toolkit (SiViT), an interactive real-time visualisation of such computational models of cell signalling networks. This research considers the available visualisation methods both within and outwith the field of biology and draws on the field of information visualisation to inform assessment of SiViT both quantitatively and qualitatively to improve usability and inform future design and development of similar software tools. Through systematic experimentation, alternative graphical interfaces were developed, including 2D and 3D approaches to rendering perspective as well as fixed and dynamically changing network layouts. The effectiveness of these interfaces was measured in terms of time to task completion, accuracy and general usability. Additionally, colour perception in the context of network visualisations and the effect of scene lighting on colour perception were explored. Results show that 2D versions perform better than 3D alternatives. However, users show a preference towards 3D variants. Layout did not affect the user performance, but, in combination with rendering perspective, resulted in some combinations that work well and others that do not. The user preference of layouts was also found to be dependent on the version of the rendering perspective it was coupled with.","abstract_html":"Cancer is one of the leading causes of death worldwide and arises from cells that do not function properly. Cell functioning is governed in part by signalling pathways within the cell that translate environmental signals detected at the cell membrane into cell behaviour. The dynamic nature and topological complexity of these pathways gives cells the ability to adapt to a wide range of perturbations and can make cells resistant to drug therapy. Systems biology models provide the means to simulate signalling pathways and their dynamics and help scientists gain a better understanding of the inner workings of cells, which informs development of anti-cancer drugs. However, signalling networks’ complexity means that models are challenging to use, and it is difficult to present simulation results effectively. The research work described in this thesis developed a Signalling Visualisation Toolkit (SiViT), an interactive real-time visualisation of such computational models of cell signalling networks. This research considers the available visualisation methods both within and outwith the field of biology and draws on the field of information visualisation to inform assessment of SiViT both quantitatively and qualitatively to improve usability and inform future design and development of similar software tools. Through systematic experimentation, alternative graphical interfaces were developed, including 2D and 3D approaches to rendering perspective as well as fixed and dynamically changing network layouts. The effectiveness of these interfaces was measured in terms of time to task completion, accuracy and general usability. Additionally, colour perception in the context of network visualisations and the effect of scene lighting on colour perception were explored. Results show that 2D versions perform better than 3D alternatives. However, users show a preference towards 3D variants. Layout did not affect the user performance, but, in combination with rendering perspective, resulted in some combinations that work well and others that do not. The user preference of layouts was also found to be dependent on the version of the rendering perspective it was coupled with.","abstract_has_math":false,"creators":["Boiko, Andrei"],"institution":"Abertay University","degree_name":"PhD","degree_level":"Doctoral Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Bown, James","Szymkowiak, Andrea"],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-10","date_published":"2020-10","updated_at":"2026-07-24T00:50:23Z","subjects":["Visualisation","Cancer","Network","Signalling pathways","Human-computer interaction"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:rke.abertay.ac.uk:studenttheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad"],"render_values":[{"text":"oai:rke.abertay.ac.uk:studenttheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad","href":null,"code":true}]}]},"links":{"outbound_url":"https://rke.abertay.ac.uk/en/studentTheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Bown, James","Szymkowiak, Andrea"]},{"key":"dc:creator","label":"Author","values":["Boiko, Andrei"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-10"]},{"key":"dc:date.issued","label":"Date","values":["2020-10"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Games Technology and Mathematics"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Abertay University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://rke.abertay.ac.uk/en/studentTheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral Thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Visualisation","Cancer","Network","Signalling pathways","Human-computer interaction"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights.embargodate","label":"Dc Rights Embargodate","values":["2026-03-23"]},{"key":"dc:rights.embargoreason","label":"Dc Rights Embargoreason","values":["/dk/atira/pure/core/document/studentthesisembargoreason/publicationissues"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:rke.abertay.ac.uk:studenttheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad","https://rke.abertay.ac.uk/en/studentTheses/758fbfc4-3858-4ad9-9b01-1475ec5f10ad"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://rke.abertay.ac.uk/files/31638765/Boiko_EvaluatingInteractiveNetworkVisualisations_PhD_2020_Redacted.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Cancer is one of the leading causes of death worldwide and arises from cells that do not function properly. Cell functioning is governed in part by signalling pathways within the cell that translate environmental signals detected at the cell membrane into cell behaviour. The dynamic nature and topological complexity of these pathways gives cells the ability to adapt to a wide range of perturbations and can make cells resistant to drug therapy. Systems biology models provide the means to simulate signalling pathways and their dynamics and help scientists gain a better understanding of the inner workings of cells, which informs development of anti-cancer drugs. However, signalling networks’ complexity means that models are challenging to use, and it is difficult to present simulation results effectively. The research work described in this thesis developed a Signalling Visualisation Toolkit (SiViT), an interactive real-time visualisation of such computational models of cell signalling networks. This research considers the available visualisation methods both within and outwith the field of biology and draws on the field of information visualisation to inform assessment of SiViT both quantitatively and qualitatively to improve usability and inform future design and development of similar software tools. Through systematic experimentation, alternative graphical interfaces were developed, including 2D and 3D approaches to rendering perspective as well as fixed and dynamically changing network layouts. The effectiveness of these interfaces was measured in terms of time to task completion, accuracy and general usability. Additionally, colour perception in the context of network visualisations and the effect of scene lighting on colour perception were explored. Results show that 2D versions perform better than 3D alternatives. However, users show a preference towards 3D variants. Layout did not affect the user performance, but, in combination with rendering perspective, resulted in some combinations that work well and others that do not. The user preference of layouts was also found to be dependent on the version of the rendering perspective it was coupled with."]},{"key":"dc:title","label":"Title","values":["Evaluating interactive network visualisations: a case study using the cell Signalling Visualisation Toolkit"]}]}],"canonical_facts":{"dc:contributor.advisor":["Bown, James","Szymkowiak, Andrea"],"dc:creator":["Boiko, Andrei"],"dc:date":["2020-10"],"dc:date.issued":["2020-10"],"dc:description.abstract":["Cancer is one of the leading causes of death worldwide and arises from cells that do not function properly. Cell functioning is governed in part by signalling pathways within the cell that translate environmental signals detected at the cell membrane into cell behaviour. The dynamic nature and topological complexity of these pathways gives cells the ability to adapt to a wide range of perturbations and can make cells resistant to drug therapy. Systems biology models provide the means to simulate signalling pathways and their dynamics and help scientists gain a better understanding of the inner workings of cells, which informs development of anti-cancer drugs. However, signalling networks’ complexity means that models are challenging to use, and it is difficult to present simulation results effectively. The research work described in this thesis developed a Signalling Visualisation Toolkit (SiViT), an interactive real-time visualisation of such computational models of cell signalling networks. This research considers the available visualisation methods both within and outwith the field of biology and draws on the field of information visualisation to inform assessment of SiViT both quantitatively and qualitatively to improve usability and inform future design and development of similar software tools. Through systematic experimentation, alternative graphical interfaces were developed, including 2D and 3D approaches to rendering perspective as well as fixed and dynamically changing network layouts. The effectiveness of these interfaces was measured in terms of time to task completion, accuracy and general usability. Additionally, colour perception in the context of network visualisations and the effect of scene lighting on colour perception were explored. Results show that 2D versions perform better than 3D alternatives. However, users show a preference towards 3D variants. Layout did not affect the user performance, but, in combination with rendering perspective, resulted in some combinations that work well and others that do not. 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