Monaco, G
(2017)
Computational approaches to study the immune system using gene expression and flow cytometry data.
PhD thesis, University of Liverpool.
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Supplement 1 - custom scripts chapter 2.zip - Unspecified Download (45kB) |
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Supplement 2 - main results co-expression.xls - Unspecified Download (3MB) |
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Supplement 3 - enrichment analysis of the genes with high and low number of CCG.xls - Unspecified Download (774kB) |
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Supplement 4 - enrichment analysis for differentially connected genes.xls - Unspecified Download (2MB) |
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Supplement 5 - Gene Sets Conservation.xls - Unspecified Download (746kB) |
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Supplement 6 - Gene sets co-expressed genes.xls - Unspecified Download (14MB) |
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Supplement 7 - custom scripts chapter 4.zip - Unspecified Download (81kB) |
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Supplement 8 - DEGs (TPM and TPM_TMM).xlsx - Unspecified Download (62MB) |
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Supplement 9 - Heatmaps (TPM).xlsx - Unspecified Download (434kB) |
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Supplement 10 -Reactome enrichment DEG and HK analysis (TMM_TPM) .xlsx - Unspecified Download (1MB) |
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Supplement 11 - Deconvolution.xlsx - Unspecified Download (1MB) |
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Text
201003652_Sep2017.pdf - Unspecified Download (19MB) |
Item Type: | Thesis (PhD) |
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Divisions: | Faculty of Health and Life Sciences > Faculty of Health and Life Sciences |
Depositing User: | Symplectic Admin |
Date Deposited: | 16 Aug 2018 08:13 |
Last Modified: | 19 Jan 2023 06:42 |
DOI: | 10.17638/03017054 |
Supervisors: |
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URI: | https://livrepository.liverpool.ac.uk/id/eprint/3017054 |
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