Services & Solutions
U.S. & China Regulatory Consulting
Navigate development and submission milestones with ExonCode Consulting LLC. Services include U.S. IND application support; pre-IND and other FDA meeting preparation; Drug Master File (DMF) submissions; NDA/ANDA submission support; Orphan Drug Designation and Fast Track designation requests; and domestic agent services for overseas marketing authorization holders (MAHs) in China. Engagements are tailored to the product, development stage, and applicable FDA or NMPA pathway.
Genomics & Custom Bioinformatics
Data-first. Algorithm-guided. Biologically grounded. We tailor NGS analysis to single-cell, spatial, bulk RNA-seq, WGS, metagenomic, and metatranscriptomic datasets. Choose the strategy your question needs: established statistical pipelines for robust comparisons; reference-guided annotation and integration; unsupervised discovery of cell states and tissue patterns; or machine learning and deep learning approaches evaluated for the dataset. Quality control, appropriate validation, interpretable outputs, and expert review connect computational results to biological context.
BiDesk | AI-Driven Analysis Platform
Bring AI-driven analysis into your research with BiDesk. Access ExonCode's dedicated platform to explore data and support scientific analysis, alongside our custom bioinformatics services. Pair AI-assisted exploration with expert interpretation to move from complex datasets toward meaningful biological questions. Explore BiDesk at app.exoncodes.com.
Clinical Genetics Analysis | CLIA/CA Platform
A dedicated platform for clinical genetic testing analysis and professional review. Connect clinical genomics data with analysis workflows that support laboratory interpretation. Clinical implementation follows laboratory-validated procedures, qualified professional oversight, and applicable CLIA and California requirements. Contact bioinfo@exoncode.com to request platform access or discuss your laboratory's workflow.
NGS & Bioinformatics Expertise
Single-Cell RNA-seq Analysis
Bulk RNA-seq & Functional Interpretation
Single-Cell RNA-seq Analysis
Resolve cellular heterogeneity with quality control, doublet assessment, normalization, dimensionality reduction, clustering, and cell-type annotation. Compare conditions with differential expression and pathway analysis; extend to trajectory analysis or cell-cell communication when appropriate to the study. Deliverables are tailored to your experimental design.
Spatial Transcriptomics
Bulk RNA-seq & Functional Interpretation
Single-Cell RNA-seq Analysis
Place gene expression in tissue context. Analyze spatial quality metrics, expression patterns, tissue domains, spatially variable genes, and regional pathway activity. Integrate single-cell references for cell-type mapping or deconvolution where supported by the assay. Connect molecular signatures with tissue architecture through interpretable visualizations.
Bulk RNA-seq & Functional Interpretation
Bulk RNA-seq & Functional Interpretation
Bulk RNA-seq & Functional Interpretation
From raw reads to biological interpretation: sequencing QC, alignment or transcript quantification, sample-level assessment, differential expression, and pathway enrichment. Study-aware statistical models account for relevant covariates and batch effects. Clear visualizations and documented methods support reproducible research and scientific communication.
Whole-Genome Sequencing Analysis
Algorithms, Data & Deep Learning Strategies
Bulk RNA-seq & Functional Interpretation
Characterize genomic variation with read QC, alignment, coverage assessment, variant calling, filtering, and annotation. Small-variant, copy-number, and structural-variant analyses are scoped to the data and research objective. Cohort comparisons and prioritized findings help focus downstream investigation, with transparent methods and documented quality metrics.
Metagenomics & Metatranscriptomics
Algorithms, Data & Deep Learning Strategies
Algorithms, Data & Deep Learning Strategies
Investigate microbial community composition, functional potential, and transcriptional activity. Workflows can include host-read removal, taxonomic profiling, diversity analysis, functional annotation, and between-group comparisons. Integrate metagenomic DNA and metatranscriptomic RNA to connect which organisms are present with the functions they express, according to study design and data quality.
Algorithms, Data & Deep Learning Strategies
Algorithms, Data & Deep Learning Strategies
Algorithms, Data & Deep Learning Strategies
Start with the scientific question, then select the right computational strategy. Combine curated public and project data, reproducible algorithms, and fit-for-purpose statistical or learning-based models. Explore deep learning for representation learning, cell-state discovery, and multi-omics integration where appropriate. Model evaluation considers held-out data, batch effects, confounding, and interpretability; expert review connects predictions to biology. Deliverables can include documented workflows, quality metrics, visualizations, and a tailored analysis report.