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The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways
Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classi...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823428/ https://www.ncbi.nlm.nih.gov/pubmed/31672983 http://dx.doi.org/10.1038/s41597-019-0193-4 |
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author | Ochsner, Scott A. Abraham, David Martin, Kirt Ding, Wei McOwiti, Apollo Kankanamge, Wasula Wang, Zichen Andreano, Kaitlyn Hamilton, Ross A. Chen, Yue Hamilton, Angelica Gantner, Marin L. Dehart, Michael Qu, Shijing Hilsenbeck, Susan G. Becnel, Lauren B. Bridges, Dave Ma’ayan, Avi Huss, Janice M. Stossi, Fabio Foulds, Charles E. Kralli, Anastasia McDonnell, Donald P. McKenna, Neil J. |
author_facet | Ochsner, Scott A. Abraham, David Martin, Kirt Ding, Wei McOwiti, Apollo Kankanamge, Wasula Wang, Zichen Andreano, Kaitlyn Hamilton, Ross A. Chen, Yue Hamilton, Angelica Gantner, Marin L. Dehart, Michael Qu, Shijing Hilsenbeck, Susan G. Becnel, Lauren B. Bridges, Dave Ma’ayan, Avi Huss, Janice M. Stossi, Fabio Foulds, Charles E. Kralli, Anastasia McDonnell, Donald P. McKenna, Neil J. |
author_sort | Ochsner, Scott A. |
collection | PubMed |
description | Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus ‘omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org. |
format | Online Article Text |
id | pubmed-6823428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68234282019-11-07 The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways Ochsner, Scott A. Abraham, David Martin, Kirt Ding, Wei McOwiti, Apollo Kankanamge, Wasula Wang, Zichen Andreano, Kaitlyn Hamilton, Ross A. Chen, Yue Hamilton, Angelica Gantner, Marin L. Dehart, Michael Qu, Shijing Hilsenbeck, Susan G. Becnel, Lauren B. Bridges, Dave Ma’ayan, Avi Huss, Janice M. Stossi, Fabio Foulds, Charles E. Kralli, Anastasia McDonnell, Donald P. McKenna, Neil J. Sci Data Article Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus ‘omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org. Nature Publishing Group UK 2019-10-31 /pmc/articles/PMC6823428/ /pubmed/31672983 http://dx.doi.org/10.1038/s41597-019-0193-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ochsner, Scott A. Abraham, David Martin, Kirt Ding, Wei McOwiti, Apollo Kankanamge, Wasula Wang, Zichen Andreano, Kaitlyn Hamilton, Ross A. Chen, Yue Hamilton, Angelica Gantner, Marin L. Dehart, Michael Qu, Shijing Hilsenbeck, Susan G. Becnel, Lauren B. Bridges, Dave Ma’ayan, Avi Huss, Janice M. Stossi, Fabio Foulds, Charles E. Kralli, Anastasia McDonnell, Donald P. McKenna, Neil J. The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
title | The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
title_full | The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
title_fullStr | The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
title_full_unstemmed | The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
title_short | The Signaling Pathways Project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
title_sort | signaling pathways project, an integrated ‘omics knowledgebase for mammalian cellular signaling pathways |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823428/ https://www.ncbi.nlm.nih.gov/pubmed/31672983 http://dx.doi.org/10.1038/s41597-019-0193-4 |
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