Omics sciences such as metabolomics, lipidomics, and proteomics support animal science research by enabling molecular-level characterization of biological systems and production-relevant phenotypes. These approaches help investigate nutrition-related metabolism, host-environment interactions, and molecular signatures associated with health-related traits in livestock and companion animals. In applied R&D settings, omics data can contribute to evidence generation for feed formulation, production efficiency studies, food quality assessment, and welfare-related monitoring frameworks.
Lipid metabolism in animal health:
Molecular profiling of lipid species associated with metabolic dysregulation, adiposity-related phenotypes, and inflammation-linked pathways in animal models and cohorts.
Nutritional lipidomics:
Assessment of lipid intake and fatty-acid composition in feed programs to support productivity, fertility-related traits, and immune-related endpoints in research studies.
Milk and meat quality characterization:
Lipid composition analysis in dairy and meat matrices to support nutritional profiling, quality attributes, and comparability assessments.
Lipid-based biomarker research:
Discovery and evaluation of lipid signatures associated with infectious or metabolic phenotypes for research and monitoring applications.
Environmental impact on lipid homeostasis:
Assessment of diet, climate, and housing-related variables and their association with lipid metabolism using multi-factor experimental designs.
Metabolic biomarker research for monitoring applications:
Identification of metabolic signatures associated with early-stage signal detection and longitudinal monitoring in livestock and companion animal research.
Compound/xenobiotic response characterization:
Evaluation of metabolic pathway modulation following exposure to test articles or xenobiotics to support safety-related pathway analysis and R&D decision-making.
Nutrition optimization studies:
Metabolic profiling to inform diet formulation studies linked to growth, reproduction-related traits, and immune-related readouts.
Food safety and residue/contaminant monitoring:
Detection and trending of residues, mycotoxins, and contaminants in animal-derived food matrices to support analytical surveillance programs.
Stress and welfare-related profiling:
Metabolic signatures associated with welfare-relevant endpoints to support management and husbandry optimization studies.
Infectious disease research and immunology-focused R&D:
Protein-level characterization of host and pathogen systems to support antigen discovery workflows and immune-response research.
Protein biomarker research for monitoring applications:
Evaluation of protein signatures associated with health-related traits to support research monitoring and longitudinal study designs.
Nutritional proteomics:
Protein digestion, absorption, and utilization profiling to support feed and formulation research.
Meat and milk proteomics:
Protein composition analysis to support quality attributes, authenticity testing, and comparability assessments.
Genetic and breed-related molecular characterization:
Proteomic variation studies across breeds/lines to support selection programs and productivity-related research endpoints.
At oloBion, we provide cutting-edge omics services designed to empower researchers in the Veterinary & Animal Science industry. With our state-of-the-art technology and the expertise of our team, we help you unlock the full potential of your analytes, driving discovery, innovation, and impactful solutions. Our portfolio includes both Untargeted and Targeted metabolomics, lipidomics and proteomics services, as well as ADME-DMPK assays, all tailored to meet the specific needs of your research.
Technique: LC-MS/MS
Untargeted lipidomics analysis for the identification of lipids by LC-MS/MS.The Identification includes a list with superclass, class, lipid name, and InChIKey.
Technique: LC-MS/MS
Untargeted lipidomics analysis for the identification of short chain fatty acids by LC-MS/MS. The indentification includes a list with superclass, class, lipid name, and InChIKey.
Technique: LC-MS/MS
Untargeted lipidomics analysis for the identification of lipids by LC-MS/MS, including oxylipins. The Identification includes a list with superclass, class, lipid name, and InChIKey.
Technique: LC-MS/MS
Untargeted lipidomics analysis for the identification of lipids by LC-MS/MS.The Identification includes a list with superclass, class, lipid name, and InChIKey.
Pharmacolipidomics analysis to identify key lipid classes and determine lipid biomarkers related to bioavailability, metabolism, and compound response, supporting ADME and mechanistic evaluation in preclinical studies.
Targeted lipidomics analysis for the quantification of total fatty acids (FW) (g/100g)
Technique: LC-MS/MS
Target Lipidomics analysis for the identification of specific lipid(s) according to customer requirements
Technique: LC-MS/MS
NextGen proteomics analysis by LC-MS/MS for the identification of proteins in plasma. The identification includes the family and name of the protein.
Technique: LC-MS/MS
NextGen proteomics analysis by LC-MS/MS for the identification of proteins in stool. The identification includes the family and name of the protein.
Technique: LC-MS/MS
NextGen proteomics analysis by LC-MS/MS for the identification of proteins. The identification includes the family and name of the protein.
Pharmacoproteomics analysis to identify key proteins and determine proteomic biomarkers related to drug metabolism, transport, and resistance mechanisms, supporting mechanistic insight in preclinical research.
Technique: LC-MS/MS
Target Proteomics analysis for the identification of specific protein(s) according to customer requirements
Pharmacoproteomics analysis to identify key proteins and determine proteomic biomarkers related to drug metabolism, transport, and resistance mechanisms, supporting mechanistic insight in preclinical research.
Pharmacolipidomics analysis to identify key lipid classes and determine lipid biomarkers related to bioavailability, metabolism, and compound response, supporting ADME and mechanistic evaluation in preclinical studies.
Pharmacometabolomics studies to identify key metabolic pathways and determine metabolomic biomarkers associated with compound exposure and metabolic response, supporting ADME and mechanistic insight in preclinical research.
Transform your omics data into actionable insights with oloMAP Portal, our interactive platform for advanced statistical analysis and visualization.
Combine multiple omics datasets to uncover relationships between biological layers, gain a holistic view of underlying processes and identify potential biomarkers.
Comprehensive biological interpretation from our experts to connect omics data with biological pathways, highlighting relevant mechanisms and potential biomarkers tailored to your study.
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Mass Spectrometry
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oloMAP Portal
Standard Delivery Time:
6 weeks
Fast-track option available
Minimum Sample Amount:
Consult our experts for guidance
on sample requirements
Discount:
Associated with the number of
samples and multi-omics analysis
Partner with us to explore the power of omics in your field. Our team is ready to guide you through the process and deliver insights tailored to your research or industry needs.
Contact us today to discuss your project or schedule a consultation. Together, we’ll advance innovation through omics!