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Image by National Institute of Allergy and Infectious Diseases

Key Focus:
BIOMARKER DISCOVERY

Biomarker discovery is transforming the future of early detection, precision therapy, and personalized medicine. Whether you’re identifying prognostic gene signatures, tracking disease progression, or validating companion diagnostics, next-generation sequencing (NGS) delivers the resolution and scale to explore biomarkers across the genome, transcriptome, and epigenome.

Turning Molecular Signals Into Clinical Breakthroughs

01

Identify differentially expressed genes or transcripts

02

Detect somatic variants and rare mutations linked to disease or resistance

03

Discover methylation and other epigenetic signatures

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Stratify patient cohorts by molecular profiles

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Track treatment response via cfDNA or RNA biomarkers

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Validate biomarker panels for clinical trial or diagnostic use

07

Profile immune signatures with TCR/BCR sequencing

Why Biomarker Discovery Needs NGS

Biomarkers are measurable molecular indicators of biological states—genetic variants, RNA expression profiles, or epigenetic patterns that signal health, disease, or therapeutic response. The discovery process involves identifying and validating these signals by comparing datasets from healthy versus diseased individuals, responders versus non-responders, or different disease stages.

  • Genomic biomarkers: germline variants, somatic mutations, copy number alterations

  • Transcriptomic biomarkers: gene expression changes, alternative splicing, fusion transcripts

  • Epigenetic biomarkers: DNA methylation, histone modifications, chromatin accessibility patterns

  • Multi-omic biomarkers: integrated DNA, RNA, and epigenetic signatures

By providing unbiased, high-throughput, and quantitative data, NGS enables biomarker discovery that’s faster, more comprehensive, and more reproducible than ever before.

From oncology and neurology to immunology and infectious disease, biomarkers are reshaping how researchers detect, diagnose, and manage disease. Genetic variants can predict inherited risk, RNA expression profiles can reveal early-stage cancers, and cfDNA in liquid biopsies can monitor minimal residual disease long before clinical symptoms appear.

How We Support AG Research

  • Oncology: Tumor mutation profiling, cfDNA-based minimal residual disease tracking, companion diagnostic validation

  • Neurology: Gene expression and methylation signatures for neurodegenerative and psychiatric disorders

  • Infectious Disease: Host–pathogen transcriptomics and immune response biomarkers

  • Immunology & Vaccine Research: Immune repertoire analysis and predictive immune response modeling

  • Rare Disease & Complex Traits: Integrative multi-omic discovery of novel pathogenic markers

 

Explore our tailored sequencing solutions for biomarker discovery, including:

Whole Exome Sequencing (WES) · cfDNA Sequencing · RNA Sequencing · Methylation Profiling · Single-Cell Analysis

Advantages of Working with AUGenomics

At AUGenomics, we collaborate with research teams advancing the next generation of precision diagnostics and therapeutics.

We offer:

  • Tailored workflows for challenging sample types and complex study designs

  • Multi-omic integration across DNA, RNA, and epigenetic datasets

  • Rapid turnaround — data delivery in as little as 3–5 days for select assays

  • Transparent communication through real-time project updates

  • Proven innovation — from XPrize-winning assay development to pioneering biomarker applications

Our approach is designed to empower discovery, not just deliver data.

Where Genomics Meets Discovery

Modern biomarker discovery is powered by genomics. High-throughput sequencing technologies enable the detection of subtle molecular patterns across thousands of samples, revealing new pathways and mechanisms of disease.

At AUGenomics, we combine comprehensive sequencing with advanced computational and machine learning approaches to uncover biomarkers that traditional methods often miss. Our team integrates genomic, transcriptomic, and epigenetic data to identify predictive signatures that translate directly into clinical and translational insights.

Machine learning models amplify discovery by finding nonlinear relationships and subtle molecular fingerprints that accelerate biomarker validation, stratify patient cohorts, and enhance diagnostic accuracy.

Image by Dan Meyers

Your Partner In Biomarker Discovery

Accelerate your discoveries with fast, reliable, and tailored next-gen sequencing services built for breakthrough results.

Let’s Work Together

Get in touch so we can start working together.

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