Systems biology approaches to finding novel pain mediators.
Chronic pain represents a major health burden; this maladaptive pain state occurs as a consequence of hypersensitivity within the peripheral and central components of the somatosensory system. High throughput technologies (genomics, transciptomics, lipidomics, and proteomics) are now being applied t...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2013
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| _version_ | 1797066012135260160 |
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| author | Antunes-Martins, A Perkins, JR Lees, J Hildebrandt, T Orengo, C Bennett, D |
| author_facet | Antunes-Martins, A Perkins, JR Lees, J Hildebrandt, T Orengo, C Bennett, D |
| author_sort | Antunes-Martins, A |
| collection | OXFORD |
| description | Chronic pain represents a major health burden; this maladaptive pain state occurs as a consequence of hypersensitivity within the peripheral and central components of the somatosensory system. High throughput technologies (genomics, transciptomics, lipidomics, and proteomics) are now being applied to tissue derived from pain patients as well as experimental pain models to discover novel pain mediators. The use of clustering, meta-analysis and other techniques can help refine potential candidates. Of particular importance are systems biology methods, such as co-expression network generating algorithms, which infer potential associations/interactions between molecules and build networks based on these interactions. Protein-protein interaction networks allow the lists of potential targets generated by these different platforms to be analyzed in their biological context. Outputs from these different methods must also be related to the clinical pain phenotype. The improved and standardized phenotyping of pain symptoms and sensory signs enables much better subject stratification. Our hope is that, in the future, the use of computational approaches to integrate datasets including sensory phenotype as well as the outputs of high throughput technologies will help define novel pain mediators and provide insights into the pathogenesis of chronic pain. |
| first_indexed | 2024-03-06T21:36:21Z |
| format | Journal article |
| id | oxford-uuid:46654df6-16f0-47e5-9fd8-5c434e8a0397 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T21:36:21Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:46654df6-16f0-47e5-9fd8-5c434e8a03972022-03-26T15:13:23ZSystems biology approaches to finding novel pain mediators.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:46654df6-16f0-47e5-9fd8-5c434e8a0397EnglishSymplectic Elements at Oxford2013Antunes-Martins, APerkins, JRLees, JHildebrandt, TOrengo, CBennett, DChronic pain represents a major health burden; this maladaptive pain state occurs as a consequence of hypersensitivity within the peripheral and central components of the somatosensory system. High throughput technologies (genomics, transciptomics, lipidomics, and proteomics) are now being applied to tissue derived from pain patients as well as experimental pain models to discover novel pain mediators. The use of clustering, meta-analysis and other techniques can help refine potential candidates. Of particular importance are systems biology methods, such as co-expression network generating algorithms, which infer potential associations/interactions between molecules and build networks based on these interactions. Protein-protein interaction networks allow the lists of potential targets generated by these different platforms to be analyzed in their biological context. Outputs from these different methods must also be related to the clinical pain phenotype. The improved and standardized phenotyping of pain symptoms and sensory signs enables much better subject stratification. Our hope is that, in the future, the use of computational approaches to integrate datasets including sensory phenotype as well as the outputs of high throughput technologies will help define novel pain mediators and provide insights into the pathogenesis of chronic pain. |
| spellingShingle | Antunes-Martins, A Perkins, JR Lees, J Hildebrandt, T Orengo, C Bennett, D Systems biology approaches to finding novel pain mediators. |
| title | Systems biology approaches to finding novel pain mediators. |
| title_full | Systems biology approaches to finding novel pain mediators. |
| title_fullStr | Systems biology approaches to finding novel pain mediators. |
| title_full_unstemmed | Systems biology approaches to finding novel pain mediators. |
| title_short | Systems biology approaches to finding novel pain mediators. |
| title_sort | systems biology approaches to finding novel pain mediators |
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