Biogenity

𝗢𝗹𝗶𝗻𝗸 𝗣𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗶𝗻 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗯𝗹𝗲 𝗹𝗮𝗿𝗴𝗲-𝗰𝗼𝗵𝗼𝗿𝘁 𝘀𝘁𝘂𝗱𝗶𝗲𝘀
Large cohort studies place high demands on assay robustness and reproducibility. Olink technology is designed to deliver consistent results across runs, operators, and study sizes.

Biogenity supports Olink proteomics projects ranging from pilot studies to large-scale cohorts, ensuring standardized workflows and quality control throughout. This consistency is essential for studies approaching translational or clinical phases.

Planning a large cohort or longitudinal study? Let’s talk about reproducibility, scale, and workflow design.

🔗 https://biogenity.com/olink-proteomics

⚡️ 𝗔𝗺𝗶𝗻𝗼 𝗮𝗰𝗶𝗱 𝗮𝗻𝗱 𝗲𝗻𝗲𝗿𝗴𝘆 𝗺𝗲𝘁𝗮𝗯𝗼𝗹𝗶𝘀𝗺
Amino acids and energy-related metabolites sit at the core of metabolism. Their levels reflect how cells use nutrients, generate energy, and respond to changing physiological demands.

By quantifying amino acids, acylcarnitines, and TCA cycle intermediates, this analysis provides a direct view of mitochondrial function and metabolic balance. These pathways are often among the first to shift in response to diet, stress, disease, or altered energy demand.

At Biogenity, this platform is used when the goal is to understand metabolic state at a fundamental level, rather than focusing on a single downstream pathway.

💬 If energy balance or mitochondrial function is central to your study, let’s discuss whether this analysis fits.

🔗 https://biogenity.com/metabolomics/amino-acid-and-energy-metabolism

🧬 𝗢𝗹𝗶𝗻𝗸 𝗣𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗶𝗻 𝗰𝗼𝗻𝘁𝗿𝗼𝗹𝗹𝗲𝗱 𝘀𝗮𝗺𝗽𝗹𝗲 𝗵𝗮𝗻𝗱𝗹𝗶𝗻𝗴
Pre-analytical variation is a major source of noise in proteomics. Standardized sample handling and preparation are essential for generating reliable data.

Biogenity emphasizes controlled workflows for Olink proteomics, offering both partial and complete sample preparation services. Centralized handling helps minimize technical variability and improve data comparability across samples and studies.

Unsure about sample preparation or logistics? Let’s discuss best practices for Olink proteomics workflows.

🔗 https://biogenity.com/olink-proteomics

🍊 𝗩𝗶𝘁𝗮𝗺𝗶𝗻𝘀 𝗮𝗻𝗱 𝗰𝗼𝗳𝗮𝗰𝘁𝗼𝗿𝘀 𝗶𝗻 𝘀𝗲𝗻𝘀𝗶𝘁𝗶𝘃𝗲 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝗮𝗹 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀
Measuring vitamins and cofactors is analytically demanding. Many of these compounds are sensitive to light, oxidation, and temperature, and small handling differences can affect data quality.

At Biogenity, vitamin and cofactor analyses are performed using validated, stability-focused workflows and targeted LC-MS/MS and GC-MS/MS platforms. Sample preparation is optimized to preserve labile compounds and ensure reproducibility across diverse matrices, from biological fluids to tissues, food, and fermentation samples.

This approach supports reliable interpretation in nutritional, clinical, environmental, and systems biology studies.

💬 Planning a study involving labile metabolites like vitamins or cofactors? Let’s discuss analytical strategy and workflow design early on.

🔗 https://biogenity.com/metabolomics

🔬 𝗣𝗲𝗽𝘁𝗶𝗱𝗼𝗺𝗶𝗰𝘀 𝗶𝗻 𝗯𝗶𝗼𝗺𝗮𝗿𝗸𝗲𝗿 𝗮𝗻𝗱 𝗲𝗽𝗶𝘁𝗼𝗽𝗲 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆
Peptides are often directly linked to biological function, acting as signaling molecules, epitopes, or bioactive fragments. This makes peptidomics a valuable approach for biomarker discovery and studies focused on immune-related processes, allergens, or antigen presentation.

Peptidomics can be applied as a stand-alone analysis or integrated with broader proteomics studies to add resolution at the peptide level. This combination supports the interpretation of how mutations, cellular perturbations, or disease states alter the proteomic landscape beyond protein abundance alone.

At Biogenity, peptidomics is used when peptide-level detail is required to answer biologically specific questions.

💬 Working on peptide biomarkers, epitopes, or immune-related targets? Let’s discuss how peptidomics can complement your study.

🔗 https://biogenity.com/peptidomics

🧬 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗽𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗶𝗻 𝗱𝗶𝘀𝗲𝗮𝘀𝗲 𝗯𝗶𝗼𝗹𝗼𝗴𝘆
Clinical proteomics is used when protein-level information is needed to understand disease states, prognosis, or treatment response. By profiling the proteome across patient samples, it supports biomarker discovery and the development of models for patient stratification and personalized medicine.

At Biogenity, clinical proteomics is applied in studies ranging from exploratory biomarker discovery to cohort-based analyses. Combined with bioinformatics, protein profiling enables the identification of disease-associated patterns and protein signatures relevant for clinical research.

This approach is particularly valuable when the goal is to link molecular data with clinical phenotypes and outcomes.

💬 Working with clinical samples and protein biomarkers? Let’s discuss whether clinical proteomics fits your study design.

🔗 https://biogenity.com/clinical-proteomics

🗺️ 𝗢𝗹𝗶𝗻𝗸 𝗣𝗿𝗼𝘁𝗲𝗼𝗺𝗶𝗰𝘀 𝗶𝗻 𝗵𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗶𝘀-𝗱𝗿𝗶𝘃𝗲𝗻 𝗮𝗻𝗱 𝗲𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗼𝗿𝘆 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵
Olink offers a broad portfolio of panels targeting inflammation, oncology, neurology, cardiovascular biology, metabolism, and cell regulation. This flexibility supports both hypothesis-driven studies and broader exploratory research designs.

At Biogenity, panel selection is guided by the underlying biological question, disease context, and study objectives. Aligning panel choice with scientific intent is critical for generating interpretable and impactful results.

Not sure which Olink panel fits your research question? Let’s discuss panel strategy and study alignment.

🔗 https://biogenity.com/olink-proteomics

🧬 𝗟𝗶𝗽𝗶𝗱 𝗺𝗲𝘁𝗮𝗯𝗼𝗹𝗶𝘀𝗺 𝗶𝗻 𝗿𝗼𝗯𝘂𝘀𝘁 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝗮𝗹 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀
Lipid analysis presents specific analytical challenges. Many lipid classes are sensitive to oxidation, temperature, and extraction conditions, making workflow design critical for data quality.

At Biogenity, lipid metabolism analyses are performed using validated, class-specific workflows optimized to preserve lipid integrity across diverse sample types. Using LC–MS/MS and GC–MS/MS platforms, we deliver reproducible, quantitative data across fatty acids, phospholipids, lipid mediators, bile acids, and related compounds.

This approach supports consistent interpretation across studies ranging from basic research to translational and exposure-focused projects.

Planning a lipidomics study and want to discuss analytical strategy early on? Let’s talk through workflow and panel selection.

🔗 https://biogenity.com/metabolomics