AI-driven bioinformatics for ageing and age-associated diseases
Core Expertise
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AI-driven bioinformatics and systems biology
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Host–microbiome interaction analysis
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Computational biology of ageing and age-associated diseases
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Multi-omics data integration and network-based modelling
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Translational analysis of metabolic and disease-relevant pathways
Research
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AI-guided Microbiome Biotechnology for Healthy Ageing
We develop AI-driven bioinformatics and systems biology approaches to design and validate microbiome-based biotechnological interventions targeting age-related metabolic decline. Our focus is on mechanistic host–microbiome interactions and established metabolic endpoints (e.g., glucose dynamics and inflammatory readouts) to support preventative strategies for healthy ageing and age-associated disease risk.
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Computational Biology of Ageing
Computational analysis of genetic and molecular mechanisms of ageing and age-related diseases, with a focus on how ageing-driven biological changes contribute to metabolic and disease susceptibility. We apply systems biology, network-based models, and integrative bioinformatics approaches to support hypothesis generation and mechanistic insight.
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Multi-omics for Drug Discovery and Target Identification
Integration and analysis of multi-omics datasets to characterise disease-associated molecular networks and pathways. Our approaches support early-stage target prioritisation and hypothesis generation in ageing-associated diseases and cancer, enabling translational research collaborations.
Larisa Atanasiu, PhD
Founder & Scientific Lead
Redwood Genetics
Fulbright Alumna
Redwood Genetics is a research-driven biotechnology company engaged in collaborative research projects with academic institutions, hospitals, and research organisations, particularly within EU-funded programmes.
