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Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo

The ability to detect activation of signaling pathways based solely on gene expression data represents an important goal in biological research. We tested the sensitivity of singular value decomposition-based regression by focusing on functional interactions between the Ras and transforming growth f...

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Autores principales: Liu, Zhandong, Wang, Min, Alvarez, James V, Bonney, Megan E, Chen, Chien-chung, D'Cruz, Celina, Pan, Tien-chi, Tadesse, Mahlet G, Chodosh, Lewis A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2646284/
https://www.ncbi.nlm.nih.gov/pubmed/19094238
http://dx.doi.org/10.1186/gb-2008-9-12-r180
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author Liu, Zhandong
Wang, Min
Alvarez, James V
Bonney, Megan E
Chen, Chien-chung
D'Cruz, Celina
Pan, Tien-chi
Tadesse, Mahlet G
Chodosh, Lewis A
author_facet Liu, Zhandong
Wang, Min
Alvarez, James V
Bonney, Megan E
Chen, Chien-chung
D'Cruz, Celina
Pan, Tien-chi
Tadesse, Mahlet G
Chodosh, Lewis A
author_sort Liu, Zhandong
collection PubMed
description The ability to detect activation of signaling pathways based solely on gene expression data represents an important goal in biological research. We tested the sensitivity of singular value decomposition-based regression by focusing on functional interactions between the Ras and transforming growth factor beta signaling pathways. Our findings demonstrate that this approach is sufficiently sensitive to detect the secondary activation of endogenous signaling pathways as it occurs through crosstalk following ectopic activation of a primary pathway.
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spelling pubmed-26462842009-02-23 Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo Liu, Zhandong Wang, Min Alvarez, James V Bonney, Megan E Chen, Chien-chung D'Cruz, Celina Pan, Tien-chi Tadesse, Mahlet G Chodosh, Lewis A Genome Biol Method The ability to detect activation of signaling pathways based solely on gene expression data represents an important goal in biological research. We tested the sensitivity of singular value decomposition-based regression by focusing on functional interactions between the Ras and transforming growth factor beta signaling pathways. Our findings demonstrate that this approach is sufficiently sensitive to detect the secondary activation of endogenous signaling pathways as it occurs through crosstalk following ectopic activation of a primary pathway. BioMed Central 2008 2008-12-18 /pmc/articles/PMC2646284/ /pubmed/19094238 http://dx.doi.org/10.1186/gb-2008-9-12-r180 Text en Copyright © 2008 Liu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method
Liu, Zhandong
Wang, Min
Alvarez, James V
Bonney, Megan E
Chen, Chien-chung
D'Cruz, Celina
Pan, Tien-chi
Tadesse, Mahlet G
Chodosh, Lewis A
Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
title Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
title_full Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
title_fullStr Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
title_full_unstemmed Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
title_short Singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
title_sort singular value decomposition-based regression identifies activation of endogenous signaling pathways in vivo
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2646284/
https://www.ncbi.nlm.nih.gov/pubmed/19094238
http://dx.doi.org/10.1186/gb-2008-9-12-r180
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