Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA

Yitan Zhu; Zuyi Wang; Yuanjian Feng; Jianhua Xuan; David J. Miller; Eric P. Hoffman; Yue Wang

doi:10.1109/IEMBS.2006.260031

Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA

Yitan Zhu, Zuyi Wang, Yuanjian Feng, Jianhua Xuan, David J. Miller, Eric P. Hoffman, Yue Wang

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, VIsual Statistical Data Analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic conditions. We then superimpose existing knowledge of gene regulation and gene function (Ingenuity Pathway Analysis) to analyze the clustering results and generate novel hypotheses for further research on muscular dystrophies.

Original language	English (US)
Title of host publication	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Pages	5767-5770
Number of pages	4
DOIs	https://doi.org/10.1109/IEMBS.2006.260031
State	Published - 2006
Event	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States Duration: Aug 30 2006 → Sep 3 2006

Publication series

Name	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)	0589-1019

Other

Other	28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Country/Territory	United States
City	New York, NY
Period	8/30/06 → 9/3/06

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/IEMBS.2006.260031

Cite this

Zhu, Y., Wang, Z., Feng, Y., Xuan, J., Miller, D. J., Hoffman, E. P., & Wang, Y. (2006). Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA. In 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 (pp. 5767-5770). Article 4029547 (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings). https://doi.org/10.1109/IEMBS.2006.260031

@inproceedings{d763c3bd29174d4e994345355a0cbe0b,

title = "Phenotypic-specific gene module discovery using a diagnostic tree and caBIG{\texttrademark} VISDA",

abstract = "For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, VIsual Statistical Data Analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic conditions. We then superimpose existing knowledge of gene regulation and gene function (Ingenuity Pathway Analysis) to analyze the clustering results and generate novel hypotheses for further research on muscular dystrophies.",

author = "Yitan Zhu and Zuyi Wang and Yuanjian Feng and Jianhua Xuan and Miller, {David J.} and Hoffman, {Eric P.} and Yue Wang",

year = "2006",

doi = "10.1109/IEMBS.2006.260031",

language = "English (US)",

isbn = "1424400325",

series = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

pages = "5767--5770",

booktitle = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06",

note = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 ; Conference date: 30-08-2006 Through 03-09-2006",

}

Zhu, Y, Wang, Z, Feng, Y, Xuan, J, Miller, DJ, Hoffman, EP & Wang, Y 2006, Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA. in 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06., 4029547, Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, pp. 5767-5770, 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, United States, 8/30/06. https://doi.org/10.1109/IEMBS.2006.260031

Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA. / Zhu, Yitan; Wang, Zuyi; Feng, Yuanjian et al.
28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06. 2006. p. 5767-5770 4029547 (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA

AU - Zhu, Yitan

AU - Wang, Zuyi

AU - Feng, Yuanjian

AU - Xuan, Jianhua

AU - Miller, David J.

AU - Hoffman, Eric P.

AU - Wang, Yue

PY - 2006

Y1 - 2006

N2 - For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, VIsual Statistical Data Analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic conditions. We then superimpose existing knowledge of gene regulation and gene function (Ingenuity Pathway Analysis) to analyze the clustering results and generate novel hypotheses for further research on muscular dystrophies.

AB - For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, VIsual Statistical Data Analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic conditions. We then superimpose existing knowledge of gene regulation and gene function (Ingenuity Pathway Analysis) to analyze the clustering results and generate novel hypotheses for further research on muscular dystrophies.

UR - http://www.scopus.com/inward/record.url?scp=34047149302&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34047149302&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2006.260031

DO - 10.1109/IEMBS.2006.260031

M3 - Conference contribution

C2 - 17946331

AN - SCOPUS:34047149302

SN - 1424400325

SN - 9781424400324

T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

SP - 5767

EP - 5770

BT - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06

T2 - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06

Y2 - 30 August 2006 through 3 September 2006

ER -

Zhu Y, Wang Z, Feng Y, Xuan J, Miller DJ, Hoffman EP et al. Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA. In 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06. 2006. p. 5767-5770. 4029547. (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings). doi: 10.1109/IEMBS.2006.260031

Phenotypic-specific gene module discovery using a diagnostic tree and caBIG™ VISDA

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this