Biomarker Xplorer

2. Discovery of Biomarkers

Identification of expression profiles via Bulk RNA-Seq or Single-cell RNA-Seq to reveal molecular signatures associated with your conditions of interest

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Applications:

• Detection and characterization of biomarkers from global or targeted transcriptomic analyses

• Comparison of experimental groups (patients vs controls, treated vs untreated, etc.) to identify differentially expressed genes (DEGs) and molecular signatures associated with pathologies, treatments, or biological states

• Adaptable to a wide variety of sample types: tissues, cell cultures, blood, biofilms, etc.

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Techniques:

• Bulk RNA-Seq: for global expression profiling of complex samples

• Single-cell RNA-Seq: to explore cellular heterogeneity and identify specific subpopulations or rare molecular signatures

• Dedicated bioinformatics analysis: to identify DEGs, explore enriched signaling pathways, and highlight associated biological signatures

• Systematic quality control of data (RNA RIN/RQN, sequencing quality, mapping and expression metrics)

3. Integrated Bioinformatics and Multi-omics Analysis

Integrated bioinformatics and multi-omics analyses to uncover molecular signatures and biological pathways with precision.

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Applications:

• Integration of genomic, transcriptomic, and proteomic data for a holistic interpretation of biological mechanisms

• Identification of molecular signatures associated with diseases, therapeutic responses, or physiological states

• Comparative analyses across cohorts, conditions, or treatments

• Functional interpretation of multi-omics datasets to discover biomarkers and biological pathways of interest

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Techniques:

• NGS data processing pipelines: quality control, trimming, alignment, and quantification

• Multi-omics integration approaches: combining DNA, RNA, and protein data for cross-layer interpretation

• Differential analysis and clustering: identification of discriminant features across groups

• Functional annotation & pathway enrichment: leveraging reference databases (GO, KEGG, Reactome, STRING)

• Exploratory statistics and data visualization: PCA, heatmaps, networks, and dimensionality reduction plots

• Custom bioinformatics reporting: standardized outputs, interactive visualizations, and publication-ready figures

4. Validation of Targeted Biomarkers

Confirmation of differential expression of identified biomarkers using qPCR, NanoString, or other suitable technologies

Applications:

• Validation of molecular signatures or candidate genes selected after RNA-Seq or Single-cell RNA-Seq

• Comparative analysis of gene expression across experimental groups (disease, treatment, biological conditions, etc.)

• Accurate quantification of gene expression of targets of interest in additional samples or extended cohorts

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Techniques:

• qPCR (endpoint or real-time RT-qPCR): rapid and sensitive validation of biomarker expression

• dPCR (digital PCR): ultra-sensitive and absolute quantification of biomarker expression, particularly suited for rare transcripts, circulating DNA/RNA, or low-concentration samples; ideal for clinical or preclinical applications requiring very low detection thresholds

• FlowCytometry or Imaging (Confocal Microscopy)

• Western Blot / ELISA: biomarker validation at the protein level when required

• Systematic quality control of samples and data (purity, concentration, reverse transcription efficiency, standard curves, internal controls)