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Vasiliou Laboratory (V-Lab)
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INFORMATION FOR

YARR - Yale Alcohol Research Resource

Our NIAAA-funded R24 Resource Center is dedicated to advancing alcohol research by providing cutting-edge resources and expertise to investigators in the field. The services offered are structured around three specific aims:

Transgenic Mouse Models

We maintain and provide access to unique populations of transgenic mouse models highly relevant to alcohol metabolism and oxidative stress. These include global knockout, knockin, and tissue-specific knockout strains for key genes in alcohol metabolism, such as Adh1, Aldh1a1, Aldh1b1, Aldh2, Aldh3a1, Cat, and Cyp2e1, as well as genes involved in antioxidant defense systems like Gclc, Gclm, and Nrf2. Upon request, we can generate new mouse models using advanced CRISPR techniques. These models are available to NIAAA-funded investigators to support their research on the pathogenesis of alcohol-related diseases.

Please send inquiries and requests to: Dr. Ying Chen, Dr. Vasilis Vasiliou

Advanced Metabolomics Analyses

We offer sophisticated metabolomics analyses, including both targeted (based on our large in-house library), untargeted workflows, and large-scale metabolomics analyses. We also offer MALDI imaging mass spectrometry (IMS) for spatial analysis of metabolites within tissue samples. This service includes consultation on experimental design, data collection, and collaboration opportunities to help researchers better understand the molecular mechanisms of alcohol-induced tissue damage. Our expertise is particularly advantageous for interpreting complex data, due to our experience on both metabolomics and alcohol biology, a service not typically available through commercial providers.

Please send inquiries and requests to: Dr. Georgia Charkoftaki, Dr. Vasilis Vasiliou

Machine Learning for Complex Data Analysis

  • We provide advanced machine learning (ML) services to help uncover and interpret complex relationships within large datasets associated with alcohol research. This includes the integration of diverse data sources (e.g., multi-omics and clinical data) and ML/artificial intelligence (AI) to identify critical molecular pathways, and predictive modeling to facilitate the development of precision interventions and risk assessment. These services are designed to reveal associations that may be missed by standard statistical approaches, offering new insights into alcohol-induced diseases.
  • Please see a relative publication from the team. “Charkoftaki, G., Aalizadeh, R., Santos-Neto, A. et al. An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model. Hum Genomics 17, 80 (2023).”

Please send inquiries and requests to: Dr. Reza Aalizadeh, Dr. Vasilis Vasiliou

Our resource center is committed to supporting the broader alcohol research community by making these resources widely accessible, not only within Yale but also to external investigators. Our goal is to enhance research capabilities, drive innovation, and ultimately improve understanding of alcohol's impact on health.