Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia

Quang Vinh Nguyen; Andrew Gleeson; Nicholas Ho; Mao Lin Huang; Simeon J. Simoff; Daniel R. Catchpoole

doi:10.1007/978-3-642-24955-6_14

Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia

Quang Vinh Nguyen, Andrew Gleeson, Nicholas Ho, Mao Lin Huang, Simeon J. Simoff, Daniel R. Catchpoole

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

13 Citations (Scopus)

Abstract

![CDATA[This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.]]

Original language	English
Title of host publication	Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I
Publisher	Springer
Pages	113-120
Number of pages	8
ISBN (Print)	9783642249549
DOIs	https://doi.org/10.1007/978-3-642-24955-6_14
Publication status	Published - 2011
Event	ICONIP (Conference) - Duration: 1 Jan 2011 → …

Publication series

Name
ISSN (Print)	0302-9743

Conference

Conference	ICONIP (Conference)
Period	1/01/11 → …

Keywords

data mining
gene expression
information visualisation
lymphoblastic leukemia
medical informatics
microarray analysis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-642-24955-6_14

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Nguyen, Q. V., Gleeson, A., Ho, N., Huang, M. L., Simoff, S. J., & Catchpoole, D. R. (2011). Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia. In Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I (pp. 113-120). Springer. https://doi.org/10.1007/978-3-642-24955-6_14

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title = "Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia",

abstract = "![CDATA[This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.]]",

keywords = "data mining, gene expression, information visualisation, lymphoblastic leukemia, medical informatics, microarray analysis",

author = "Nguyen, {Quang Vinh} and Andrew Gleeson and Nicholas Ho and Huang, {Mao Lin} and Simoff, {Simeon J.} and Catchpoole, {Daniel R.}",

year = "2011",

doi = "10.1007/978-3-642-24955-6_14",

language = "English",

isbn = "9783642249549",

publisher = "Springer",

pages = "113--120",

booktitle = "Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I",

note = "ICONIP (Conference) ; Conference date: 01-01-2011",

}

Nguyen, QV, Gleeson, A, Ho, N, Huang, ML, Simoff, SJ & Catchpoole, DR 2011, Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia. in Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I. Springer, pp. 113-120, ICONIP (Conference), 1/01/11. https://doi.org/10.1007/978-3-642-24955-6_14

Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia. / Nguyen, Quang Vinh; Gleeson, Andrew; Ho, Nicholas et al.
Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I. Springer, 2011. p. 113-120.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia

AU - Nguyen, Quang Vinh

AU - Gleeson, Andrew

AU - Ho, Nicholas

AU - Huang, Mao Lin

AU - Simoff, Simeon J.

AU - Catchpoole, Daniel R.

PY - 2011

Y1 - 2011

N2 - ![CDATA[This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.]]

AB - ![CDATA[This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.]]

KW - data mining

KW - gene expression

KW - information visualisation

KW - lymphoblastic leukemia

KW - medical informatics

KW - microarray analysis

UR - http://handle.uws.edu.au:8081/1959.7/512877

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DO - 10.1007/978-3-642-24955-6_14

M3 - Conference Paper

SN - 9783642249549

SP - 113

EP - 120

BT - Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I

PB - Springer

T2 - ICONIP (Conference)

Y2 - 1 January 2011

ER -

Visual analytics of clinical and genetic datasets of acute lymphoblastic leukaemia

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Keywords

UN SDGs

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