Genetic sequences: tracing the mutations of a disease.

Conference poster

Mitchell, I., Passmore, P. and Xu, K. 2010. Genetic sequences: tracing the mutations of a disease. IEEE VAST Symposium 2010 Challenge. Salt Lake City, Utah, USA 24 - 29 Oct 2010
TypeConference poster
TitleGenetic sequences: tracing the mutations of a disease.
AuthorsMitchell, I., Passmore, P. and Xu, K.
Abstract

The entry is to address the mini challenge 3 in the IEEE VAST Challenge 2010. A patient, identified by Interpol as Nicolai Kuryakin, is admitted to a hospital in Paris after being removed from a flight to Moscow due to illness. The patient, now deceased, was admitted with an unidentified illness and later developed symptoms consistent with Drafa Fever. An autopsy confirmed the presence of the Drafa virus in the patient’s bloodstream. Visual analytics methods are applied to help to understand the evolution of the current Drafa virus outbreak, as it may shed some light on Nicolai’s contacts.

Research GroupArtificial Intelligence group
ConferenceIEEE VAST Symposium 2010 Challenge
Publication process dates
Deposited21 Feb 2011
Output statusPublished
LanguageEnglish
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Xu, K., Yu, Q., Liu, Q., Zhang, J. and Bouguettaya, A. 2011. Web service management system for bioinformatics research: a case study. Service Oriented Computing and Applications. 5 (1), pp. 1-15. https://doi.org/10.1007/s11761-011-0076-9
A knowledge discovery service system for provenance exploration
Liu, Q., Zhang, J., James, F., Xu, K. and Dinesh, N. 2011. A knowledge discovery service system for provenance exploration. International Conference on Data and Knowledge Engineering (ICDKE) 2011. Milan, Italy 06 - 08 Sep 2011
Integration of geographic information system and RADARSAT synthetic aperture radar data using a self-organizing map network as compensation for realtime ground data in automatic image classification
Shepherd, I., Passmore, P. and Kamal, M. 2010. Integration of geographic information system and RADARSAT synthetic aperture radar data using a self-organizing map network as compensation for realtime ground data in automatic image classification. Journal of Applied Remote Sensing. 4 (1), pp. 1-13. https://doi.org/10.1117/1.3457166
Statistical analysis for brain EIT images using SPM.
Zhang, Y., Passmore, P., Yerworth, R. and Bayford, R. 2005. Statistical analysis for brain EIT images using SPM. Institute of Electrical and Electronics Engineers. pp. 60-67 https://doi.org/10.1109/MEDIVIS.2005.17
Models of cell assembly decay
Passmore, P. and Huyck, C. 2008. Models of cell assembly decay. Institute of Electrical and Electronics Engineers. pp. 1-6 https://doi.org/10.1109/UKRICIS.2008.4798946
Visualization of multidimensional and multimodal tomographic medical imaging data, a case study
Zhang, Y., Passmore, P. and Bayford, R. 2009. Visualization of multidimensional and multimodal tomographic medical imaging data, a case study. Philosophical Transactions of the Royal Society of London. A: Mathematical and Physical Sciences. 367 (1900), pp. 3121-3148. https://doi.org/10.1098/rsta.2009.0084
Seeing more than the graph: evaluation of multivariategraph visualization methods.
Cunningham, A., Xu, K. and Thomas, B. 2010. Seeing more than the graph: evaluation of multivariategraph visualization methods. Santucci, G. (ed.) Association for Computing Machinery (ACM). pp. 429 https://doi.org/10.1145/1842993.1843106
Invariance of visual perception
Chikhman, V., Shelepin, Y., Foreman, N., Passmore, P., Vakhrameeva, O. and Pronin, S. 2008. Invariance of visual perception. Experimental Psychology. 1, pp. 7-33.
Viewpoint invariance in the recognition of 3-D depth-rotated figures
Chikhman, V., Shelepin, Y., Foreman, N. and Passmore, P. 2008. Viewpoint invariance in the recognition of 3-D depth-rotated figures. Perception. 37.
The estimation of quantitative ranges of invariance in visual perception
Chikhman, V., Shelepin, Y., Vakhrameeva, O., Pronin, S., Foreman, N. and Passmore, P. 2009. The estimation of quantitative ranges of invariance in visual perception. Perception. 38.
A connectionist inference model for pattern-directed knowledge representation
Mitchell, I. and Bavan, A. 2000. A connectionist inference model for pattern-directed knowledge representation. Expert Systems. 17 (2), pp. 106-113.
Quality assurance of curricula through the use of an integrated framework for programme validation.
Mitchell, I., Sheriff, M. and Georgiadou, E. 2008. Quality assurance of curricula through the use of an integrated framework for programme validation. Tempus JEP-27178-2006, Dissemination Workshop.. Yerevan, Armenia Sep 2008
Task based visualization of 5D brain EIT data
Zhang, Y., Passmore, P. and Bayford, R. 2009. Task based visualization of 5D brain EIT data. SAC09: The 2009 ACM Symposium on Applied Computing. Honolulu Hawaii, USA 08 - 12 Mar 2009 New York Association for Computing Machinery (ACM). pp. 831-835 https://doi.org/10.1145/1529282.1529459
Selection enthusiasm.
Mitchell, I. and Agrawal, A. 2006. Selection enthusiasm. in: 6th International Conference on Simulated Evolutionand Learning, Hefei, China. Proceedings. Heidelberg Springer Verlag.
Dynamics in proportionate selection.
Mitchell, I., Agrawal, A., Litovski, I. and Passmore, P. 2005. Dynamics in proportionate selection. in: International Conference on Adaptive and Natural Computnig Alogorithms, Coimbra, Portugal. Proceedings. Vienna. Springer. pp. 226-229
Colour vision model-based approach for segmentation of traffic signs
Gao, X., Hong, K., Passmore, P., Podladchikova, L. and Shaposhnikov, D. 2008. Colour vision model-based approach for segmentation of traffic signs. EURASIP Journal on Image and Video Processing. 2008. https://doi.org/10.1155/2008/386705
MESSM: a framework for protein fold recognition using neural networks and support vector machines.
Mitchell, I., Jiang, N. and Wu, W. 2006. MESSM: a framework for protein fold recognition using neural networks and support vector machines. International Journal of Bioinformatics Research and Applications. 2 (4), pp. 381-393. https://doi.org/10.1504/IJBRA.2006.011037
Threading with environment-specific score by artificial neural networks
Mitchell, I., Jiang, N. and Wu, W. 2006. Threading with environment-specific score by artificial neural networks. Soft Computing. 10 (4), pp. 305-314. https://doi.org/10.1007/s00500-005-0488-6
Visualization and post-processing of 5D Brain Images
Zhang, Y., Passmore, P. and Bayford, R. 2005. Visualization and post-processing of 5D Brain Images. 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Shanghai, China 01 - 04 Sep 2005 IEEE. pp. 1083-1086 https://doi.org/10.1109/IEMBS.2005.1616607