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What is the Target 96 Development Panel
Customized panel for developmental biology
The Olink Target 96 Development Panel is a high-performance tool designed for protein analysis, offering the ability to analyze 92 key protein biomarkers from just 1μL of biological samples. This panel focuses on proteins that are essential for understanding biological processes, with a particular emphasis on their roles in development. The biomarkers included have been carefully selected for their relevance to various developmental stages and pathways. The data obtained from this panel can provide insights into biological mechanisms, such as cell migration, extracellular matrix formation, and neurogenesis.
Features of the panel
- High Sensitivity and Precision: It provides highly accurate and sensitive protein biomarker analysis, even with small sample volumes (as low as 1μL).
- Comprehensive Coverage: The panel includes 92 protein biomarkers that are carefully selected based on their roles in development-related biological processes.
- Dynamic Range: The biomarkers are chosen for their dynamic range in biological samples, ensuring reliable and reproducible results across various applications.
- Relevant to Development: The proteins included are closely related to developmental stages and biological pathways, such as cell migration, extracellular matrix formation, and neurogenesis.
- Advanced Technology: Utilizes Olink's Proximity Extension Assay (PEA) technology, which enhances the sensitivity and accuracy of protein quantification.
- Efficient Analysis: Allows for the analysis of a large number of proteins in a single run, making it a time-efficient and cost-effective solution for high-throughput research.
- Customizable for Specific Research Needs: The panel can be tailored to meet specific research requirements, providing flexibility for various developmental studies.
List of 96 Development Panel
Protein category
The Olink Target 96 Development Panel includes 96 proteins categorized into five main groups: Cell Adhesion Molecules (25), Enzymes (12), Growth Factors/Regulators (12), Miscellaneous (29), and Receptors (6), along with additional proteins classified as "others" (6). This panel encompasses a wide range of proteins involved in cell adhesion, enzymatic activity, growth regulation, receptor signaling, and other diverse biological functions. The extensive coverage of human proteins makes this panel a valuable tool for advanced biomarker discovery, disease research, and translational studies.
Table. List of Olink Target 96 Devolepment Panel
| Category | Protein | Protein ID | Protein Name |
| Cell Adhesion Molecules | P50895 | BCAM | Basal cell adhesion molecule |
| O76076 | CCN5 | CCN family member 5 | |
| P48960 | CD97 | CD97 antigen | |
| Q8TCZ2 | CD99L2 | CD99 antigen-like protein 2 | |
| Q6YHK3 | CD109 | CD109 antigen | |
| Q8N6Q3 | CD177 | CD177 antigen | |
| Q9NNX6 | CD209 | CD209 antigen | |
| Q4KMG0 | CDON | Cell adhesion molecule-related/down-regulated by oncogenes | |
| Q6UXG3 | CD300LG | CMRF35-like molecule 9 | |
| Q5KU26 | COLEC12 | Collectin-12 | |
| Q8IWV2 | CNTN4 | Contactin-4 | |
| Q13822 | ENPP2 | Ectonucleotide pyrophosphatase/phosphodiesterase family member 2 | |
| Q96AP7 | ESAM | Endothelial cell-selective adhesion molecule | |
| P19256 | CD58 | Lymphocyte function-associated antigen 3 | |
| P14174 | MIF | Macrophage migration inhibitory factor | |
| O00339 | MATN2 | Matrilin-2 | |
| Q99972 | MYOC | Myocilin | |
| Q14112 | NID2 | Nidogen-2 | |
| Q99983 | OMD | Osteomodulin | |
| Q9UKJ1 | PILRA | Paired immunoglobulin-like type 2 receptor alpha | |
| Q5VY43 | PEAR1 | Platelet endothelial aggregation receptor 1 | |
| P09619 | PDGFRB | Platelet-derived growth factor receptor beta | |
| P10586 | PTPRF | Receptor-type tyrosine-protein phosphatase F | |
| Q9Y6N7 | ROBO1 | Roundabout homolog 1 | |
| Q14162 | SCARF1 | Scavenger receptor class F member 1 | |
| O75326 | SEMA7A | Semaphorin-7A | |
| O00241 | SIRPB1 | Signal-regulatory protein beta-1 | |
| P31948 | STIP1 | Stress-induced-phosphoprotein 1 | |
| Enzymes | Q10588 | BST1 | ADP-ribosyl cyclase/cyclic ADP-ribose hydrolase 2 |
| Q9UKK9 | NUDT5 | ADP-sugar pyrophosphatase | |
| P15289 | ARSA | Arylsulfatase A | |
| P15291 | B4GALT1 | Beta-1,4-galactosyltransferase 1 | |
| O43505 | B4GAT1 | Beta-1,4-glucuronyltransferase 1 | |
| P08236 | GUSB | Beta-glucuronidase | |
| Q9UBX1 | CTSF | Cathepsin F | |
| P47712 | PLA2G4A | Cytosolic phospholipase A2 | |
| O43278 | SPINT1 | Kunitz-type protease inhibitor 1 | |
| O43291 | SPINT2 | Kunitz-type protease inhibitor 2 | |
| P00995 | SPINK1 | Serine protease inhibitor Kazal-type 1 | |
| Q9NQ38 | SPINK5 | Serine protease inhibitor Kazal-type 5 | |
| Growth Factors/Regulators | Q9BY76 | ANGPTL4 | Angiopoietin-related protein 4 |
| P11717 | IGF2R | Cation-independent mannose-6-phosphate receptor | |
| O00585 | CCL21 | C-C motif chemokine 21 | |
| O95633 | FSTL3 | Follistatin-related protein 3 | |
| P21217, Q11128 | FUT3/5 | Galactoside 3(4)-L-fucosyltransferase, Alpha-(1,3)-fucosyltransferase 3/5 | |
| Q8TDQ0 | HAVCR2 | Hepatitis A virus cellular receptor 2 | |
| P04233 | CD74 | HLA class II histocompatibility antigen gamma chain | |
| P55103 | INHBC | Inhibin beta C chain | |
| Q99538 | LGMN | Legumain | |
| P06734 | FCER2 | Low affinity immunoglobulin epsilon Fc receptor | |
| Q99497 | PARK7 | Protein deglycase DJ-1 | |
| P07237 | P4HB | Protein disulfide-isomerase | |
| Miscellaneous | P16112 | ACAN | Aggrecan core protein |
| P05067 | APP | Amyloid beta A4 protein | |
| P08118 | MSMB | Beta-microseminoprotein | |
| P00918 | CA2 | Carbonic anhydrase 2 | |
| P23280 | CA6 | Carbonic anhydrase 6 | |
| Q15828 | CST6 | Cystatin-M | |
| Q9NZV1 | CRIM1 | Cysteine-rich motor neuron 1 protein | |
| Q6UXH1 | CRELD2 | Cysteine-rich with EGF-like domain protein 2 | |
| Q02487 | DSC2 | Desmocollin-2 | |
| Q9UBP4 | DKK3 | Dickkopf-related protein 3 | |
| Q14118 | DAG1 | Dystroglycan | |
| Q07108 | CD69 | Early activation antigen CD69 | |
| P30043 | BLVRB | Flavin reductase NADPH | |
| P01215 | CGA | Glycoprotein hormones alpha chain | |
| P55808 | XG | Glycoprotein Xg | |
| Q6UXH9 | PAMR1 | Inactive serine protease PAMR1 | |
| Q14696 | MESDC2 | LDLR chaperone MESD | |
| Q6GTX8 | LAIR1 | Leukocyte-associated immunoglobulin-like receptor 1 | |
| O95721 | SNAP29 | Synaptosomal-associated protein 29 | |
| P63313 | TMSB10 | Thymosin beta-10 | |
| P04066 | FUCA1 | Tissue alpha-L-fucosidase | |
| O14773 | TPP1 | Tripeptidyl-peptidase 1 | |
| Q969Z4 | RELT | Tumor necrosis factor receptor superfamily member 19L | |
| P29350 | PTPN6 | Tyrosine-protein phosphatase non-receptor type 6 | |
| Q8TEU8 | WFIKKN2 | WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 2 | |
| Q9Y279 | VSIG4 | V-set and immunoglobulin domain-containing protein 4 | |
| Receptors | P24387 | CRHBP | Corticotropin-releasing factor-binding protein |
| Q9Y240 | CLEC11A | C-type lectin domain family 11 member A | |
| Q86T13 | CLEC14A | C-type lectin domain family 14 member A | |
| Q96RD9 | FCRL5 | Fc receptor-like protein 5 | |
| P08648 | ITGA5 | Integrin alpha-5 | |
| P05556 | ITGB1 | Integrin beta-1 | |
| P78552 | IL13RA1 | Interleukin-13 receptor subunit alpha-1 | |
| others | O43405 | COCH | Cochlin |
| Q08431 | MFGE8 | Lactadherin | |
| Q16363 | LAMA4 | Laminin subunit alpha-4 | |
| P23284 | PPIB | Peptidyl-prolyl cis-trans isomerase B | |
| P30086 | PEBP1 | Phosphatidylethanolamine-binding protein 1 | |
| P48745 | NOV | Protein NOV homolog | |
| O43464 | HTRA2 | Serine protease HTRA2, mitochondrial |
Protein Functions
Biological process
Ninety-two proteins are related to biological processes such as developmental processes, cell communication, cell adhesion, transport, immune response, cell transport, apoptosis, cell migration, and cell proliferation.
Disease area
Ninety-two proteins are implicated in research pertaining to neurological disorders, oncology, cardiovascular diseases, skeletal disorders, dermatological issues, and renal pathologies.
Kegg Pathways
Among the 92 proteins, the pathway with the highest number of enriched proteins was the Lysosome pathway, followed by Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC), ECM-Receptor Interactionamong others.
Workflow of Olink Proteomics
Demo Results of Olink Data
(Figures come from Ding, R., et al. 2024)
The bar chart displayed the number of proteins.
Volcano plots of differentially expressed proteins.
Heatmap of differentially expressed proteins.
Case Study
Plasma Proteomics Improves Prediction of Coronary Plaque Progression
Journal: European Heart Journal – Cardiovascular Imaging
Year: 2025
- Background
- Results
Coronary plaque progression is a key driver of adverse cardiovascular events in patients at risk for or with established coronary artery disease (CAD). Traditional risk factors (e.g., hypertension, diabetes) and imaging-based evaluations (such as coronary computed tomography angiography, CCTA) provide valuable prognostic information, yet they do not fully capture individual variability in plaque progression risk. This study investigates whether adding targeted plasma proteomic profiles to standard clinical risk assessments and baseline plaque measurements can more accurately predict long-term plaque progression and identify individuals at highest risk.
The study utilized the Olink Target 96 Development Panel to enhance the prediction of coronary plaque progression by integrating plasma proteomics with traditional cardiovascular risk factors. Over an average follow-up of 8.5 years, 97 participants underwent serial coronary computed tomography angiography (CCTA) and proteomic analysis to identify biomarkers associated with plaque progression. The inclusion of proteomics significantly improved predictive accuracy, particularly for percent atheroma volume (PAV) and percent non-calcified plaque volume (NCPV) progression, with the area under the curve (AUC) increasing from 0.830 to 0.909 (p = 0.023) for PAV and from 0.685 to 0.825 (p = 0.008) for NCPV. However, proteomics did not enhance the prediction of calcified plaque volume (CPV) progression. Notably, proteins such as Growth Differentiation Factor 15 (GDF-15) and Chemokine Ligand 4 (CCL4) were significantly associated with plaque development, highlighting key inflammatory and apoptotic pathways. The study demonstrates that targeted plasma proteomics using the Olink platform provides a valuable, non-invasive tool for identifying high-risk individuals, potentially reducing the need for repeated CCTA scans while improving risk stratification and treatment strategies.
Protein expression profiles using the
Olink 96 development panels. (Jordan M. Kraaijenhof, et al. 2025)
Why Creative Proteomics
Advanced Bioinformatics Expertise
Our team provides in-depth, high-precision analysis of Olink data, leveraging cutting-edge bioinformatics tools for accurate and insightful interpretations.
Wide-Ranging Research Applications
Our services support diverse research needs, from fundamental biological studies to advanced preclinical investigations, ensuring comprehensive data analysis and interpretation.
Streamlined Operations with Standardized Procedures
We implement stringent quality control measures and optimized workflows to guarantee fast, reliable, and reproducible sample analysis with minimal turnaround time.
Exceptional End-to-End Customer Assistance
Our dedicated experts provide personalized guidance and technical support throughout the entire research process, ensuring seamless and efficient project execution.
Sample Requirements
| Sample Type | Recommended Sample Size | Sample Quality | Pre-treatment and Storage | Sample Transport |
| Plasma/Serum/Body Fluid | 40µL/sample | Protein concentration: 0.5mg/ml ~ 1mg/ml | Transfer to a clean tube, aliquot into EP tubes or 96-well plates, store at -80℃ | Seal with foil, ship with dry ice |
| Tissue | ||||
| Cells | ||||
| Exosomes | ||||
| Other |
References
- Wang, C., Feng, Y., et al., (2025). Proximity extension assay revealed novel inflammatory biomarkers for follicular development and ovarian function: a prospective controlled study combining serum and follicular fluid. Frontiers in endocrinology, 16, 1525392. https://doi.org/10.3389/fendo.2025.1525392
- Kraaijenhof, J. M., Nurmohamed, N. S., et al., (2025). Plasma proteomics improves prediction of coronary plaque progression. European heart journal. Cardiovascular Imaging, 26(3), 489–499. https://doi.org/10.1093/ehjci/jeae313
- Ding, R., Wu, L., Wei, S., et al. (2024). Multi-targeted olink proteomics analyses of cerebrospinal fluid from patients with aneurysmal subarachnoid hemorrhage. Proteome science, 22(1), 11. https://doi.org/10.1186/s12953-024-00236-x