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Detecting Cancer Pathway Crosstalk with Distance Correlation

Biological pathway regulation is complex, yet it underlies the functional coordination in a cell. Cancer is a disease that is characterized by unregulated growth, driven by underlying pathway deregulation. This pathway deregulation is both within pathways and between pathways. Here, we propose a met...

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Detalles Bibliográficos
Autores principales: Sharpnack, Michael F., Huang, Kun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525273/
https://www.ncbi.nlm.nih.gov/pubmed/26306231
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author Sharpnack, Michael F.
Huang, Kun
author_facet Sharpnack, Michael F.
Huang, Kun
author_sort Sharpnack, Michael F.
collection PubMed
description Biological pathway regulation is complex, yet it underlies the functional coordination in a cell. Cancer is a disease that is characterized by unregulated growth, driven by underlying pathway deregulation. This pathway deregulation is both within pathways and between pathways. Here, we propose a method to detect inter-pathway coordination using distance correlation. Utilizing data generated from microarray experiments, we separate the genes into pathways and calculate the pairwise distance correlation between them. The result is intuitively viewed as a network of differentially dependent pathways. We find intuitive, yet surprising significant hub pathways, including glycophosphatidylinositol anchor synthesis in lung cancer.
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spelling pubmed-45252732015-08-24 Detecting Cancer Pathway Crosstalk with Distance Correlation Sharpnack, Michael F. Huang, Kun AMIA Jt Summits Transl Sci Proc Articles Biological pathway regulation is complex, yet it underlies the functional coordination in a cell. Cancer is a disease that is characterized by unregulated growth, driven by underlying pathway deregulation. This pathway deregulation is both within pathways and between pathways. Here, we propose a method to detect inter-pathway coordination using distance correlation. Utilizing data generated from microarray experiments, we separate the genes into pathways and calculate the pairwise distance correlation between them. The result is intuitively viewed as a network of differentially dependent pathways. We find intuitive, yet surprising significant hub pathways, including glycophosphatidylinositol anchor synthesis in lung cancer. American Medical Informatics Association 2015-03-23 /pmc/articles/PMC4525273/ /pubmed/26306231 Text en ©2015 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Sharpnack, Michael F.
Huang, Kun
Detecting Cancer Pathway Crosstalk with Distance Correlation
title Detecting Cancer Pathway Crosstalk with Distance Correlation
title_full Detecting Cancer Pathway Crosstalk with Distance Correlation
title_fullStr Detecting Cancer Pathway Crosstalk with Distance Correlation
title_full_unstemmed Detecting Cancer Pathway Crosstalk with Distance Correlation
title_short Detecting Cancer Pathway Crosstalk with Distance Correlation
title_sort detecting cancer pathway crosstalk with distance correlation
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525273/
https://www.ncbi.nlm.nih.gov/pubmed/26306231
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