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ON DEMAND WEBINAR

On Demand: Multiomics Tools Feature Announcement

Unlocking the Power of Multiomics with Metabolon’s Bioinformatics Platform

“Integrating multiomics data into your research is the fastest possible accelerator to achieving deeper and meaningful biological insights” – Joe Foster, Metabolon.

Multiomics Tool Now Live – Fully integrated and accessible for all research

With easier access to reference and enrichment data, combined with data harmonization and bioinformatics tools, it has never been easier to integrate and interpret multiomics data to derive new biological insights.

Metabolon are excited to announce our newest solution to integrate multiomics data within your research projects. The Multiomics Tool – part of our Integrated Bioinformatics Platform (IBP) – provides a seamless experience for investigators to upload, integrate, and analyze your multiomics data in one project.

In this webinar, Metabolon experts will demonstrate how this innovative tool can help you streamline multiomics research and extract meaningful insights from complex datasets.

What you’ll learn:

This session will provide a guided overview of the new features available within the Multiomics Tool, highlighting key functionalities, including:

  • Integrating Multiomics Data – How to upload and harmonize different omics datasets within a single research project.
  • Predictive Modelling – How to utilize logistic regression and random forest algorithms to build actionable data models.
  • Pathway Enrichment Analysis – How to explore associations of other omics pathways with your data – leveraging REACTOME to connect metabolites, genes, and proteins to biological pathways.
  • Data Visualization & Interpretation – What multiomics features are integrated and accessible within the existing bioinformatics visualization tools to streamline analysis and reporting.

Program

Agenda
Welcome & Introduction
Challenges in Multiomics Data Integration & Why It Matters
Live Demonstration: Multiomics Tool in Action
Live Q&A

Who Should Watch

  • Scientific investigators working with one or many omics datasets, looking to extract greater value from their data.
  • Translational Researchers exploring new solutions to integrate multiomics for biomarker discovery
  • Pharmaceutical & Biotech Scientists looking to optimize multiomics-driven drug development
  • Bioinformaticians & Computational Biologists exploring multiomics modeling & data visualization

Speakers

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Joe Foster, Ph.D.

Strategic Products Director, Metabolon

Joe Foster has over 15 years of experience in bioinformatics, spread across genomics, proteomics, lipidomics, and metabolomics. Joe currently serves as Metabolon’s Director of Strategic Products, helping shape the roadmap for the Integrated Bioinformatics Platform and developing Bioinformatics Professional Services that accelerate time to insight with metabolomics and multiomics data.

Prior to joining Metabolon, Joe has held a variety of positions across R&D, customer success, Sales Engineering and Business Development for prominent brands in the Life Sciences industry including, Affymetrix, Thermo Fisher Scientific, and DNAnexus. His career highlights include working with the NHS England Genomic Laboratory Hubs to implement Secure and Scalable Clinical Bioinformatics in the cloud and his work with UK Biobank and Our Future Health to deploy a best-in-class Trusted Research Environment. With a PhD in Bioinformatics from the University of Cambridge and the European Bioinformatics Institute, Joe brings a deep scientific foundation and a practical, results-focused approach to solving complex research challenges.

Why Attend?

Multiomics research is transforming our understanding of complex biological systems, yet data integration remains a critical bottleneck. With Metabolon’s Multiomics Tool, researchers can seamlessly combine multiple omics layers, perform advanced statistical modeling, and gain deeper insights into disease mechanisms and biomarker discovery.

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References

1. Zgoda-Pols, J.R., et al., Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: investigation of nicotinic acid receptor agonists. Toxicol Appl Pharmacol, 2011. 255(1): p. 48-56.

2. Bryant, J.A., et al., The impact of an oral purified microbiome therapeutic on the gastrointestinal microbiome. Nat Med, 2026. 32(1): p. 186-196

3. McGovern, B .H., et al., SER-109, an Investigational Microbiome Drugto Reduce Recurrence After Clostridioides difficile Infection: Lessons Learned From a Phase 2 Trial. Clin Infect Dis, 2021. 72(12): p. 2132-2140.

4. Feuerstadt, P., et al., SER-109, an Oral Microbiome Therapy for Recurrent Clostridioides difficile Infection. N Engl J Med, 2022. 386(3): p. 220-229.

5. Hu, Z., et al., Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer. Mol Oncol, 2025. 19(6): p. 1737-1750.

6. Butler, F.M., et al., Vegetarian Dietary Patterns and Diet-Related Metabolites Are Associated With Kidney Function in the Adventist Health Study-2 Cohort. J Ren Nutr, 2025.

7. Stanford, J., et al., Metabolomic Profiling and Diet Quality Scoring in a Randomized Crossover Trial of Healthy and Typical Dietary Patterns. Mol Nutr Food Res, 2025 . 69(23): p. e70271.

8. O’Connor, L.E., et al., Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial. J Nutr, 2023. 153(8): p. 2181-2192.

9. Fritsch, D.A., et al., Microbiome function underpins the efficacy of a fiber-supplemented dietary intervention in dogs with chronic large bowel diarrhea. BMC Vet Res, 2022. 18(1): p. 245.

10. Leal, L.N., et al., Preweaning nutrient supply improves lactation productivity and reduces the risk of culling in Holstein cows. J Dairy Sci, 2025. 108(6): p. 5875-5888.

11. Ahsin, M., et al., Soil and pasture health underlie improved beef nutrient density determined by untargeted metabolomics in Southern US grass finished beef systems. NPJ Sci Food, 2025. 9(1): p. 151.

12. Yin, W., et al., Plasma lipid profiling across species for the identification of optimal animal models of human dyslipidemia. J Lipid Res, 2012. 53(1): p. 51-65.

13. Porter, F .D., et al., Cholesterol oxidation products are sensitive and specific blood-based biomarkers for Niemann-Pick C1 disease. Sci Transl Med, 2010. 2(56): p. 56ra81.

14. Needham, B .D., et al., Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder. Biol Psychiatry, 2021. 89(5): p. 451-462

15. Li, C., et al., Estradiol and mTORC2 cooperate to enhance prostaglandin biosynthesis and tumorigenesis in TSC2-deficient LAM cells. J Exp Med, 2014. 211(1): p. 15-28.

16. Green, P.G., et al., Metabolic flexibility and reverse remodelling of the failing human heart. Eur Heart J, 2025. 46(25): p. 2422-2433.

17. Maekawa, H., et al., SGLT2 inhibition protects kidney function by SAM-dependent epigenetic repression of inflammatory genes under metabolic stress. J Clin Invest, 2025. 135(19).

18. Wu, D., et al., Integrated screens reveal that guanine nucleotide depletion, which is irreversible via targeting IMPDH2, inhibits pancreatic cancer and potentiates KRAS inhibition. Gut, 2026.

19. Schwerdtfeger, L.A., et al., Gut microbiota and metabolites are linked to disease progression in multiple sclerosis. Cell Rep Med, 2025. 6(4): p. 102055.

20. Wu, H., et al., Microbiome-metabolome dynamics associated with impaired glucose control and responses to lifestyle changes. Nat Med, 2025. 31(7): p. 2222-2231.

21. Jacobs, J.P., et al., Cognitive behavioral therapy for irritable bowel syndrome induces bidirectional alterations in the brain-gut-microbiome axis associated with gastrointestinal symptom improvement. Microbiome, 2021. 9(1): p. 236.

22. Pietzner, M., et al., Plasma metabolites to profile pathways in noncommunicable disease multimorbidity. Nat Med, 2021. 27(3): p. 471-479.

23. Faquih, T.O., et al., Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites. J Gerontol A Biol Sci Med Sci, 2025. 80(3).

24. Scherer, N., et al., Coupling metabolomics and exome sequencing reveals graded effects of rare damaging heterozygous variants on gene function and human traits. Nat Genet, 2025. 57(1): p. 193-205.

25. Holmes, Z.C., et al., Untargeted metabolomic analysis of human milk from healthy mothers reveals drivers of metabolite variability. Sci Rep, 2024. 14(1): p. 20827.

26. Titz, B., et al., Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases. Transl Vis Sci Technol, 2024. 13(6): p. 17.

27. Bloom, S.M., et al., Cysteine dependence of Lactobacillus iners is a potential therapeutic target for vaginal microbiota modulation. Nat Microbiol, 2022. 7(3): p. 434-450.

28. Leimer, E.M., et al., Lipid profile of human synovial fluid following intra-articular ankle fracture. J Orthop Res, 2017. 35(3): p. 657-666.