SeqLens
AI-Driven RNA-Seq Reanalysis & Novel Biomarker Discovery
From reading the latest science to discovering reproducible biomarkers—powered by automated reanalysis and focused ERV insights.
From reading the latest science to discovering reproducible biomarkers—powered by automated reanalysis and focused ERV insights.
RNA-seq data is exploding across thousands of studies, but it's fragmented and inconsistent. Insights remain locked in isolated datasets, and reproducibility is low. As a result, promising biomarkers are missed, slowing translational progress.
SeqLens continuously scans new publications, retrieves and standardizes the associated RNA-seq data, and reanalyzes it with a reproducible pipeline. By integrating results across studies and incorporating overlooked signals like endogenous retroviruses (ERVs), SeqLens uncovers robust, novel biomarkers ready for validation.
SeqLens continuously scans new publications, identifies relevant disease studies, and automatically retrieves associated RNA-seq datasets (e.g., GEO/SRA).
All data is reprocessed through a unified, reproducible pipeline — delivering consistent gene- and ERV-level expression profiles with complete traceability.
Biomarkers are compared across multiple cohorts and ranked by reproducibility, effect size, and biological relevance — ensuring robust insights beyond single studies.
Interactive dashboards, detailed reports, APIs, and exportable biomarker signatures provide immediate value for translational teams.
Uncovers underexplored biological signals — endogenous retroviruses (ERVs) — with real translational and therapeutic potential.
Goes beyond single papers by building biomarker signatures that are reproducible and generalizable across multiple independent cohorts.
Closes the loop from literature ingestion to data reanalysis and biomarker discovery, dramatically reducing time and manual effort.
Every output comes with complete traceability and interpretability, ensuring trust and accelerating downstream validation.
We've reanalyzed over 10 colon cancer studies in one demo pipeline—highlighting both gene- and ERV-based signatures predictive of treatment response.
Request a demo to explore the colon cancer case study and see how SeqLens transforms fragmented data into actionable biomarker insights.
The global transcriptomics market is projected to exceed $10B by 2030, with RNA-seq as its fastest-growing segment.
Biopharma is investing heavily in reproducible biomarkers to guide oncology, neurology, and aging programs. SeqLens transforms fragmented RNA-seq data into validated, cross-study insights.
Biomarker teams in oncology, translational research groups, and leading academic labs — with expansion into neurology and aging-related disease research.
To uncover reproducible, overlooked biomarkers at scale — accelerating the discovery and validation of new therapeutic targets across cancer, neurological, and aging-related diseases.
A world where every RNA-seq study contributes to faster cures.
Our team combines deep expertise in translational omics, AI/ML, and precision medicine to solve the reproducibility crisis in biomarker discovery.
Translational omics and computational biology backgrounds
Advanced machine learning and bioinformatics experience