Using Systems Biology to understand Immunosenescen
  • Using Systems Biology to Understand Immunosenescence
  • Background
    • Introduction
    • 1.1. Aging in Society and in the Individual
    • 1.2. Aging and its Molecular Mechanisms
    • 1.3.The Remodeling of the Immune System: Immunosenescence
    • 1.4. Changes in the Immune System Related to Immunosenescence
    • 1.5 Chronic Inflammation During Aging: Inflammaging
    • 1.6 The Immune Risk Phenotype (IRP)
    • 1.6. Systems Biology
  • Objectives
  • Methods
    • Overall Methodology
    • 3.1 Survey of Studies
    • 3.2. Reannotation of Probes in Microarrays
    • 3.3. Data acquisition and pre-processing
    • 3.4. Creation of age-representative samples: AgeCollapsed
    • 3.5. Detection of Highly Age-Related Transcripts: AgingGenes
    • 3.6. Lifetime Co-Expressed Transcript Analysis: AgingNet
    • 3.7. Detection of Change Points in Age-Related Modules
  • Results
    • 4.1. Survey and Data Acquisition
    • 4.2. Reannotation of Platforms
    • 4.3. AgeCollapsed Pre-Processing and Creation
    • 4.4. Assessment of the Agreement of the Relationships of Transcripts with Age between the Sexes
    • 4.5. AgingGenes and AgingNet Reviews
    • 4.6 Aging Co-Expression Network: AgingNet
  • Discussion
    • Main Regards
    • AgingGenes
    • Análise de Co-Expressão: AgingNet
  • Conclusions
    • Final Regards
  • Citations
    • References
  • Appendix
    • Supplementary Files
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Objectives

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  • Main goal
  • Secondary goals

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Main goal

Find transcriptional programs related to immunosenescence.

Secondary goals

Find transcripts with a highly age-related expression profile, called AgingGenes.

Identify network, its modules, of transcripts co-expressed throughout life, called AgingNet.

Evaluate the biological processes related to AgingGenes and AgingNet modules and how they could be associated with the immunosenescence phenotype.

Identify moments in life in which AgingGenes and AgingNet undergo changes in their transcriptional profiles.