Manifold embedding for understanding mechanisms of transcriptional regulation

Arvind Rao; Alfred O. Hero; David J. States; James Douglas Engel

doi:10.1109/GENSIPS.2006.353127

Manifold embedding for understanding mechanisms of transcriptional regulation

Arvind Rao, Alfred O. Hero, David J. States, James Douglas Engel

Bioinformatics & Computational Biology

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

2 Scopus citations

Abstract

In this paper we propose a manifold embedding methodology to integrate heterogeneous sources of genomic data for the purpose of interpretation of transcriptional regulatory phenomena and subsequent visualization. Using the Gata3 gene as an example, we ask if it is possible to determine which genes (or their products) might be potentially involved in its tissue-specific regulation - based on evidence obtained from various available data sources. Our approach is based on co-embedding of genes onto a manifold wherein the proximity of neighbors is influenced by the probability of their interaction as reported from diverse data sources - i.e. the stronger the evidence for that gene-gene interaction, the closer they are.

Original language	English (US)
Title of host publication	2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006
Pages	3-4
Number of pages	2
DOIs	https://doi.org/10.1109/GENSIPS.2006.353127
State	Published - 2006
Event	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006 - College Station, TX, United States Duration: May 28 2006 → May 30 2006

Publication series

Name	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006

Other

Other	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006
Country/Territory	United States
City	College Station, TX
Period	5/28/06 → 5/30/06

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology (miscellaneous)
Computational Theory and Mathematics
Computer Vision and Pattern Recognition
Statistics and Probability

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10.1109/GENSIPS.2006.353127

Cite this

Rao, A., Hero, A. O., States, D. J., & Engel, J. D. (2006). Manifold embedding for understanding mechanisms of transcriptional regulation. In 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006 (pp. 3-4). Article 4161748 (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006). https://doi.org/10.1109/GENSIPS.2006.353127

Manifold embedding for understanding mechanisms of transcriptional regulation. / Rao, Arvind; Hero, Alfred O.; States, David J. et al.
2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006. 2006. p. 3-4 4161748 (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006).

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

Rao, A, Hero, AO, States, DJ & Engel, JD 2006, Manifold embedding for understanding mechanisms of transcriptional regulation. in 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006., 4161748, 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006, pp. 3-4, 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006, College Station, TX, United States, 5/28/06. https://doi.org/10.1109/GENSIPS.2006.353127

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abstract = "In this paper we propose a manifold embedding methodology to integrate heterogeneous sources of genomic data for the purpose of interpretation of transcriptional regulatory phenomena and subsequent visualization. Using the Gata3 gene as an example, we ask if it is possible to determine which genes (or their products) might be potentially involved in its tissue-specific regulation - based on evidence obtained from various available data sources. Our approach is based on co-embedding of genes onto a manifold wherein the proximity of neighbors is influenced by the probability of their interaction as reported from diverse data sources - i.e. the stronger the evidence for that gene-gene interaction, the closer they are.",

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ER -

Manifold embedding for understanding mechanisms of transcriptional regulation

Abstract

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ASJC Scopus subject areas

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