Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis

Yu Chun Lin; Hsiang Yuan Yeh; Shih Wu Cheng; Von Wun Soo

doi:10.1109/BIBE.2007.4375558

Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis

Yu Chun Lin^*, Hsiang Yuan Yeh, Shih Wu Cheng, Von Wun Soo

^*Corresponding author for this work

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

6 Scopus citations

Abstract

Microarray is widely used for the cancer research and identifies different expressions for specific genes. We present a computational method for constructing cancer and normal gene regulatory networks from micorarray data based on transcription factor analysis and independency test. The web service technology is used to wrap the bioinformatics toolkits of methods and databases to automatically extract the promoter regions of DNA sequences and predict the transcription factors that regulate gene expressions. After reconstructing the gene regulatory network, the network statistical measure and network motifs extract the potential genes to compare the sub-networks between the cancer and normal gene networks. We adopt the microarray datasets from Stanford Microarray Database of prostate cancer as a target application to evaluate the methods.

Original language	English
Title of host publication	Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Pages	151-157
Number of pages	7
DOIs	https://doi.org/10.1109/BIBE.2007.4375558
State	Published - 2007
Externally published	Yes
Event	7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE - Boston, MA, United States Duration: 14 01 2007 → 17 01 2007

Publication series

Name	Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

Conference

Conference	7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Country/Territory	United States
City	Boston, MA
Period	14/01/07 → 17/01/07

Keywords

Microarray data
Network measure
Network motifs
Regulatory network
Transcription factor analysis

UN SDGs

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

Access to Document

10.1109/BIBE.2007.4375558

Cite this

Lin, Y. C., Yeh, H. Y., Cheng, S. W., & Soo, V. W. (2007). Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis. In Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE (pp. 151-157). Article 4375558 (Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE). https://doi.org/10.1109/BIBE.2007.4375558

Lin, Yu Chun ; Yeh, Hsiang Yuan ; Cheng, Shih Wu et al. / Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis. Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE. 2007. pp. 151-157 (Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE).

@inproceedings{545458e5998047f18f8c92596f45e5df,

title = "Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis",

abstract = "Microarray is widely used for the cancer research and identifies different expressions for specific genes. We present a computational method for constructing cancer and normal gene regulatory networks from micorarray data based on transcription factor analysis and independency test. The web service technology is used to wrap the bioinformatics toolkits of methods and databases to automatically extract the promoter regions of DNA sequences and predict the transcription factors that regulate gene expressions. After reconstructing the gene regulatory network, the network statistical measure and network motifs extract the potential genes to compare the sub-networks between the cancer and normal gene networks. We adopt the microarray datasets from Stanford Microarray Database of prostate cancer as a target application to evaluate the methods.",

keywords = "Microarray data, Network measure, Network motifs, Regulatory network, Transcription factor analysis",

author = "Lin, {Yu Chun} and Yeh, {Hsiang Yuan} and Cheng, {Shih Wu} and Soo, {Von Wun}",

year = "2007",

doi = "10.1109/BIBE.2007.4375558",

language = "英语",

isbn = "1424415098",

series = "Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE",

pages = "151--157",

booktitle = "Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE",

note = "7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE ; Conference date: 14-01-2007 Through 17-01-2007",

}

Lin, YC, Yeh, HY, Cheng, SW & Soo, VW 2007, Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis. in Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE., 4375558, Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE, pp. 151-157, 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE, Boston, MA, United States, 14/01/07. https://doi.org/10.1109/BIBE.2007.4375558

Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis. / Lin, Yu Chun; Yeh, Hsiang Yuan; Cheng, Shih Wu et al.
Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE. 2007. p. 151-157 4375558 (Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE).

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

TY - GEN

T1 - Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis

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AU - Yeh, Hsiang Yuan

AU - Cheng, Shih Wu

AU - Soo, Von Wun

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AB - Microarray is widely used for the cancer research and identifies different expressions for specific genes. We present a computational method for constructing cancer and normal gene regulatory networks from micorarray data based on transcription factor analysis and independency test. The web service technology is used to wrap the bioinformatics toolkits of methods and databases to automatically extract the promoter regions of DNA sequences and predict the transcription factors that regulate gene expressions. After reconstructing the gene regulatory network, the network statistical measure and network motifs extract the potential genes to compare the sub-networks between the cancer and normal gene networks. We adopt the microarray datasets from Stanford Microarray Database of prostate cancer as a target application to evaluate the methods.

KW - Microarray data

KW - Network measure

KW - Network motifs

KW - Regulatory network

KW - Transcription factor analysis

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Lin YC, Yeh HY, Cheng SW, Soo VW. Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis. In Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE. 2007. p. 151-157. 4375558. (Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE). doi: 10.1109/BIBE.2007.4375558

Comparing cancer and normal gene regulatory networks based on microarray data and transcription factor analysis

Abstract

Publication series

Conference

Keywords

UN SDGs

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