Bindley Workshop: Biological Interpretation of Metabolomics and Lipidomics Data

Winter Workshop on Biological Interpretation of Metabolomics and Lipidomics Data

Location: DLR 131 & 134
Dates: February 16–17, 2025

February 16 — Data Foundations, Lipid Structure, and Metabolic Context

9:00–9:45 a.m. — Understanding the Structure and Information in Metabolomics and Lipidomics Datasets — Priyanka Ramesh

• Organization of datasets (sample metadata, feature tables, annotation fields)
• Variable types: intensities, identifiers, metadata
• Interpreting raw vs. processed data structures

9:45–10:45 a.m. — Lipid Structure, Properties, and Roles – Part 1 — Christina R. Ferreira

• Fundamentals of lipid classification and diversity
• Linking chemical structure to physical properties

10:45–11:00 a.m. — Coffee/tea break

11:00 a.m.–12:00 p.m. — Lipid Structure, Properties, and Roles – Part 2 — Christina R. Ferreira

• Biological functions of lipid classes
• Case examples in health and disease contexts

12:00–1:00 p.m. — Lunch

1:00–2:00 p.m. — Approaches to Biological Interpretation of Lipid Profiles Generated Using MRM Analysis: Case Studies — Theresa Casey

• Data reshaping for pathway analysis
• Interpreting lipid turnover and flux
• Case studies

2:00–3:00 p.m. — Feature Selection and Feature Engineering in Mass Spectrometry: Finding the Signals That Matter — Bartek Rajwa

• Overview of machine learning approaches for lipidomics
• Feature selection, classification, and predictive modeling
• Examples from disease development studies

3:00–3:15 p.m. — Coffee/tea break

3:15–4:15 p.m. — Small Molecule Profiling Analysis in Toxic Insult Models — Jonathan Shannahan

• Biomarkers of toxic exposure
• Integration into toxicology workflows
• Dose–response interpretation

4:15–4:45 p.m. — Day 1 wrap-up and open Q&A

February 17 — Spatial and Integrative Biological Interpretation

9:00–9:45 a.m. — Lipid Ontology — Christina R. Ferreira

• Ontology systems for lipid annotation and data integration

9:45–10:30 a.m. — Overlay of Morphological and Chemical Data in Spatial Analysis — Weiwei Zhang

• Integrating histology with metabolomics and lipidomics to interpret spatial patterns

10:30–11:15 a.m. — Specific Pathway Analysis Using Spatial Metabolomics — Wagner Tamagno

• Pathway-level interpretation from spatial metabolomics datasets
• Mapping metabolic flux and localization in tissues

11:15–11:30 a.m. — Coffee/tea break

11:30 a.m.–12:00 p.m. — Cardinal MS Application to Spatial Metabolomics Data Analysis — Julie Brothwell

• Spatial metabolomics workflows using Cardinal MS

12:00–12:45 p.m. — High-Throughput Profiling: Biological Insights from Automated DESI-MS — Nicolás Morato

• Profiling disease and biological condition markers in a biological context

12:45–1:45 p.m. — Lunch

1:45–2:15 p.m. — Integrative Panel Discussion: From Data to Biological Insight

• All speakers; linking molecular data to biological meaning

2:45–3:15 p.m. — Guided Group Exercise: Full Interpretation Workflow

• Teams analyze a case dataset combining untargeted, targeted, and spatial data

3:15–3:30 p.m. — Coffee/tea break

3:30–4:00 p.m. — Workshop Synthesis and Closing Remarks

• Summary of key points, feedback, and networking