Interaction based functional clustering of genomic data

Ritesh Krishna, Chang Tsun Li, Vicky Buchanan-Wollaston

Research output: Book chapter/Published conference paperConference paper

1 Citation (Scopus)

Abstract

We present the first report on Granger causality based detection of functional modules from temporal gene expression data. The approach uses temporal causal relationships shared between pair of genes to derive a connection matrix, which is further analyzed using graph-theoretic techniques. The approach is evaluated against a synthesized dataset and a real biological dataset obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature.

Original languageEnglish
Title of host publicationProceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
Pages130-137
Number of pages8
DOIs
Publication statusPublished - 2009
Event2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 - Taichung, Taiwan, Province of China
Duration: 22 Jun 200924 Jun 2009

Conference

Conference2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
CountryTaiwan, Province of China
CityTaichung
Period22/06/0924/06/09

Fingerprint

Gene expression
Cluster Analysis
Genes
Arabidopsis
Causality
Gene Expression
Datasets

Cite this

Krishna, R., Li, C. T., & Buchanan-Wollaston, V. (2009). Interaction based functional clustering of genomic data. In Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 (pp. 130-137). [5211305] https://doi.org/10.1109/BIBE.2009.28
Krishna, Ritesh ; Li, Chang Tsun ; Buchanan-Wollaston, Vicky. / Interaction based functional clustering of genomic data. Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. pp. 130-137
@inproceedings{0cac090730ba4fafa4dea54ad1fb8f63,
title = "Interaction based functional clustering of genomic data",
abstract = "We present the first report on Granger causality based detection of functional modules from temporal gene expression data. The approach uses temporal causal relationships shared between pair of genes to derive a connection matrix, which is further analyzed using graph-theoretic techniques. The approach is evaluated against a synthesized dataset and a real biological dataset obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature.",
author = "Ritesh Krishna and Li, {Chang Tsun} and Vicky Buchanan-Wollaston",
year = "2009",
doi = "10.1109/BIBE.2009.28",
language = "English",
isbn = "9780769536569",
pages = "130--137",
booktitle = "Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009",

}

Krishna, R, Li, CT & Buchanan-Wollaston, V 2009, Interaction based functional clustering of genomic data. in Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009., 5211305, pp. 130-137, 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009, Taichung, Taiwan, Province of China, 22/06/09. https://doi.org/10.1109/BIBE.2009.28

Interaction based functional clustering of genomic data. / Krishna, Ritesh; Li, Chang Tsun; Buchanan-Wollaston, Vicky.

Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. p. 130-137 5211305.

Research output: Book chapter/Published conference paperConference paper

TY - GEN

T1 - Interaction based functional clustering of genomic data

AU - Krishna, Ritesh

AU - Li, Chang Tsun

AU - Buchanan-Wollaston, Vicky

PY - 2009

Y1 - 2009

N2 - We present the first report on Granger causality based detection of functional modules from temporal gene expression data. The approach uses temporal causal relationships shared between pair of genes to derive a connection matrix, which is further analyzed using graph-theoretic techniques. The approach is evaluated against a synthesized dataset and a real biological dataset obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature.

AB - We present the first report on Granger causality based detection of functional modules from temporal gene expression data. The approach uses temporal causal relationships shared between pair of genes to derive a connection matrix, which is further analyzed using graph-theoretic techniques. The approach is evaluated against a synthesized dataset and a real biological dataset obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature.

UR - http://www.scopus.com/inward/record.url?scp=70449367245&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70449367245&partnerID=8YFLogxK

U2 - 10.1109/BIBE.2009.28

DO - 10.1109/BIBE.2009.28

M3 - Conference paper

AN - SCOPUS:70449367245

SN - 9780769536569

SP - 130

EP - 137

BT - Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009

ER -

Krishna R, Li CT, Buchanan-Wollaston V. Interaction based functional clustering of genomic data. In Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. p. 130-137. 5211305 https://doi.org/10.1109/BIBE.2009.28