From Raw Data to Scientific Discovery
We build complete data solutions, from robust processing pipelines that handle complex biotech data to interactive dashboards that help researchers explore and understand results. Processing and visualization working together to accelerate your research.
Let's talkStep 1: Processing Results
Every analytical technology generates unique data challenges. We specialize in building processing solutions that understand the nuances of your instrument, your data format, and your analytical goals. Our processing pipelines convert raw biotech data into clean, quantified results ready for visualization and analysis.
Mass Spectrometry Data Processing
We build pipelines that convert raw MS files into quantified results. Peak detection, isotope pattern matching, charge state deconvolution, and peptide/protein identification. We handle the full workflow for proteomics, metabolomics, and small molecule analysis.
Genomics and Sequencing Analysis
From raw sequencing reads to variant calls and gene expression matrices. We build alignment pipelines, quality filtering, variant annotation, and expression quantification workflows that scale to large sample sets.
Multi-Omics Integration
When datasets from proteomics, metabolomics, and genomics intersect, powerful discoveries emerge. We build integration pipelines that align data across modalities, handle batch effects, and prepare datasets for systems-level analysis.
Quality Control and Normalization
Raw data is rarely analysis-ready. We implement QC protocols: removing outliers, normalizing across batches, handling missing values, and applying corrections that make your data statistically sound and biologically meaningful.
Why Custom Processing Matters
Off-the-shelf tools work for standard analyses, but biotech research often pushes boundaries. Custom pipelines give you the flexibility to handle instrument quirks, incorporate domain knowledge, and optimize for your specific scientific questions.
Tailored to Your Data
Whether you're processing vendor or open source instrument outputs, we build pipelines that understand your specific file formats, metadata, and analytical requirements.
Reproducible and Validated
Scientific integrity matters. Our pipelines include version control, parameter tracking, validation against known standards, and audit trails so you can confidently defend your processing methods in any context, from publications to audits.
Scalable and Fast
One sample or ten thousand. We architect pipelines with cloud infrastructure and parallel processing that grow with your data volume. What takes hours on a laptop can run in minutes on scalable systems.
Continuous Improvement
As you discover new analytical techniques or expand your research scope, your processing pipeline evolves. We maintain and update pipelines over time, incorporating new methods and handling emerging data types.
Processing Methodology
We don't just write code. We collaborate with your scientific team to understand your research questions, instrument capabilities, and data challenges. This domain expertise ensures our pipelines are both technically sound and scientifically meaningful.
Analysis Workflow Design
We map out your entire analysis, from raw instrument output to publication-ready results. Each step is designed to maintain data integrity, handle edge cases, and provide transparency into what happened to your data.
Technology Selection
Python for statistical work, Nextflow for workflow orchestration, Docker for reproducibility, AWS for scalability. We select the right tools for each piece of your pipeline and ensure they work together seamlessly.
Implementation and Testing
We develop using agile sprints, testing against known samples and edge cases. Your team reviews results at each stage. By launch, the pipeline has been validated against real data and integrated with your workflows.
Documentation and Training
We provide comprehensive documentation so your team understands the pipeline logic, knows how to run it, and can troubleshoot issues. Training sessions ensure your researchers can confidently use and interpret results.
Step 2: Visualization
Processed data is only useful if researchers can understand and explore it. We design custom visualizations that work with your processed datasets, reveal patterns at a glance, and enable interactive exploration without requiring programming expertise.
Our visualization tools transform processed data into clear, actionable insights. From multi-omics dashboards to genomic browsers and statistical analysis panels, we create interfaces that accelerate discovery.
Multi-omics Dashboards
Explore multi-omic data interactively: view spectra, compare sequences, and analyze identifications. Drill down from overview to raw data details without losing context or performance.
Genomics and Expression Browsers
Interactive genome browsers, sequence alignment viewers, gene expression heatmaps, and volcano plots. Enable researchers to navigate complex genomic datasets, zoom into regions of interest, and compare samples intuitively.
Network and Pathway Visualization
Visualize metabolic pathways, protein interaction networks, and complex biological relationships. Interactive force-directed layouts, filtering, and highlighting help researchers identify key nodes and connections.
Statistical Analysis Dashboards
Multi-panel dashboards combining data distribution plots, statistical summaries, quality metrics, and comparative analysis. Help your team spot trends, identify outliers, and make evidence-based decisions.
Why Visualization Completes Your Data Solution
Processing cleans and quantifies your data. Visualization lets researchers explore and understand it. Together, they form a complete workflow that accelerates discovery. Processing ensures data quality, visualization enables insight.
Domain Expertise
Proteomics, genomics, metabolomics. Each discipline has unique visualization needs. We understand the conventions, best practices, and edge cases specific to your field.
Interactive
Researchers need to ask questions of their data interactively: filter, zoom, highlight, compare. We build interfaces that respond instantly and let insights emerge through exploration, not static reports.
Optimized
Thousands of data points, hundreds of samples. We optimize visualizations for responsiveness using WebGL, data binning, and smart rendering so interactions remain snappy even with large datasets.
Publication-Ready
Export high-resolution or vector-based figures, interactive HTML reports, or embeddable visualizations. Your dashboards can support discovery, validation, and communication of results.
Visualization Methodology
We design for your researchers, not ourselves. Through user research, iterative design, and testing with real data, we create interfaces that feel natural and accelerate scientific insight discovery.
Discovery and Design
We interview your research team to understand their workflows, pain points, and analytical questions. Sketches and prototypes validate design direction before engineering begins.
Iterative Development
We build in sprints, showing you functional prototypes every two weeks. Your feedback shapes the direction. By launch, the interface matches your team's mental models and workflows.
Testing with Real Data
We test visualizations with your actual datasets, including edge cases, large sample sets, and unusual distributions. Performance and clarity are validated before deployment.
Support and Evolution
Launch is just the beginning. We provide documentation, train your team, and support enhancements as your analytical needs evolve or new research questions emerge.
Complete Data Solutions for Biotech Research
Ready to transform raw data into insights? From processing to visualization, we build complete solutions tailored to your research. Let's discuss your data challenges.
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