Accelerate assay design and biomarker discovery with curated gene expression target lists built for translational and clinical research. The Gene Expression Reference Target Portfolio is a growing collection of AI-assisted, expert-curated target gene sets designed to support focused panel development across oncology, immunology, and cell therapy applications.
Our reference portfolios span a wide range of disease areas and biological applications, including hematological malignancies such as ALL, AML, MDS, MPN, Multiple Myeloma, NHL, and mastocytosis, as well as solid tumors including bladder, brain/glioma, breast, colorectal, endometrial, hepatocellular, head and neck, melanoma, NSCLC, ovarian, pancreatic, and prostate cancers. Cross-indication and functional biology collections include CAR-T cell therapy, drug resistance, immune profiling, and additional translational research applications.
Each target set is curated using a combination of:
- Commercially available assays and reference panels
- Public genomic and transcriptomic databases
- Peer-reviewed scientific literature
- AI-assisted prioritization and annotation workflows
These curated portfolios are designed to help researchers rapidly identify biologically relevant targets, streamline custom panel development, and explore disease-specific pathways with confidence.
Explore the Gene Expression Reference Target Portfolio Access curated target gene lists to support your next assay design, translational study, or biomarker discovery program. Contact our team or download the collection to get started.
Frequently Asked Questions
1. What is the Gene Expression Reference Target Portfolio? The Gene Expression Reference Target Portfolio is an expanding collection of AI-assisted, expert-curated gene sets designed to accelerate assay design and biomarker discovery. These portfolios cover a broad spectrum of research areas, including hematological malignancies (such as AML and MDS), solid tumors (like NSCLC and melanoma), and functional biology applications like CAR-T cell therapy and immune profiling.
2. How are the gene targets in these portfolios selected? To ensure biological relevance and confidence, each target set is curated through a multi-layered process. This includes analyzing commercially available assays, public genomic and transcriptomic databases, peer-reviewed scientific literature, and utilizing AI-assisted prioritization and annotation workflows to identify the most impactful markers for translational and clinical research.
3. Why is single-cell transcriptomic profiling better than bulk RNA sequencing? Bulk RNA sequencing provides an average signal of all cells in a sample, which often masks critical biological insights. In conditions like AML or MDS, bulk sequencing cannot distinguish between different cell populations such as leukemic stem cells (LSCs) and progenitors. Single-cell profiling allows you to see the "clonal architecture" by identifying exactly which transcriptional states are driving disease and resistance within individual cells.
4. How does the Tapestri platform connect genotype to phenotype? The Tapestri platform uniquely enables the simultaneous detection of mutation status (such as FLT3-ITD, IDH1/2, and NPM1) and transcriptional state within the same single cell. By linking genotype directly to cell identity and differentiation state, researchers can better understand how specific mutations drive blast populations, influence therapy response, and lead to the expansion of resistant subpopulations at relapse.