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DC Field | Value | Language |
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dc.date.accessioned | 2022-04-11T09:49:10Z | - |
dc.date.available | 2022-04-11T09:49:10Z | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | Caruana, S. (2008). BioNET : traversing and visualising biological reaction networks (Bachelor's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/93325 | - |
dc.description | B.SC.ICT(HONS)ARTIFICIAL INTELLIGENCE | en_GB |
dc.description.abstract | Accurately traversing biological reaction networks, or metabolic pathways, is a multifaceted problem. It is affected by issues involved in representing the pathways, textually as well as graphically. Furthermore the traversal is in itself a combinatorial optimisation problem. To this day not much work has been done in trying to solve this issue. This thesis targets the traversal problem through the use of the Ant Colony Optimisation metaheuristic. A three dimensional layout of the graph is rendered so that results can be animated. Furthermore a heuristic based on shadow casting principles is presented, providing a means by which to observe the animation in an optimal manner. This will effectively target the problems involved in visualising such networks. It will be shown how the traversal algorithm proves to be an effective approach to this combinatorial optimisation problem. Furthermore, the simple concept of shadow casting is shown to achieve optimal performance in visualising the network. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Motion perception (Vision) | en_GB |
dc.subject | Computer algorithms | en_GB |
dc.subject | Metaheuristics | en_GB |
dc.title | BioNET : traversing and visualising biological reaction networks. | en_GB |
dc.type | bachelorThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information & Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Caruana, Stephen (2008) | - |
Appears in Collections: | Dissertations - FacICT - 1999-2009 Dissertations - FacICTAI - 2002-2014 |
Files in This Item:
File | Description | Size | Format | |
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B.SC.(HONS)IT_Caruana_Stephen_2008.pdf Restricted Access | 6.56 MB | Adobe PDF | View/Open Request a copy |
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