Bioinformatics

Ageing is a complex biological process that impacts organisms across all layers of biological organization, from changes in individual macromolecules and metabolites through to cellular, tissue, organ and systems dysfunction. These changes occur in the context of intricate networks of cause and consequence, integrating genetic, lifestyle and environmental factors and ultimately determining individual health outcomes. Ageing is therefore intrinsically a multi-scale, multi-systems phenomenon and understanding it requires integrative -omics and multi-omics approaches. Omics techniques, such as genomics, transcriptomics, proteomics, lipidomics and metabolomics, provide snapshots of organismal state during ageing. As our understanding of ageing deepens, researchers are increasingly leveraging computational and machine learning tools to integrate -omics data and to extract and unravel mechanisms underlying ageing. This synergy between computational tools and omics data allows us to pinpoint molecular mechanisms of ageing, build predictive models and ageing “clocks”, identify potential therapeutic targets, and pave the way for personalized interventions that will ultimately benefit individuals and societies by increasing both human healthspan and lifespan.

The Healthy Longevity Translational Research Programme Bioinformatics Core (HLTRP-BIC) aims to provide infrastructure support, high-level expertise and individualized training to new and existing researchers wishing to employ -omics techniques and computational tools in the context of their projects. An important aspect of our work is to connect researchers seeking to employ omics, bioinformatics and computational tools with those members of the HLTRP who have relevant expertise and experience. Existing expertise at the HLTRP encompasses genomics, transcriptomics, lipidomics, and proteomics as well as analysis of large-scale biomedical datasets using standard statistical, machine learning computational tools.