Computational methods
Deterministic classification, evidence handling, phenotype-driven prioritisation and methodologies for nuclear, mitochondrial and structural variation.
Intelligence for Genomics
We build the products genomic science needs to scale.
From a VCF to a clinical report
Folklore brings classification, evidence, phenotype and prioritisation into one case view. A qualified professional reviews the final interpretation.
- Panels, exomes and whole genomes
- Classification, evidence and prioritisation
- Model-assisted interpretation under clinical review
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undertoneMove from a GWAS to a testable biological hypothesis
Undertone turns a complete GWAS into ranked loci, fine-mapping, candidate genes, tissues and mechanism hypotheses.
- Whole-study analysis and automatic locus discovery
- Fine-mapping, colocalization and regulatory evidence
- Private, reproducible reports with complete provenance
noodleA living map of scientific literature
Noodle helps you discover biomedical research by meaning, explore connected publications and discuss scientific questions and papers with an active community of researchers.
- Semantic discovery across biomedical literature
- Discuss scientific questions and publications
- Join an active community of researchers
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EVIDENCE
Publish the study. Let readers test the decisions
Evidence presents methods, results, sensitivity analyses and source files as one versioned study. Readers can change documented analytical decisions and see how the evidence moves.
- Versioned study releases
- Interactive sensitivity checks
- GitHub-linked data and code
We build computational methods, genomic infrastructure and clinical systems
Helena brings together genomic methodology, high-performance computing and clinical software engineering. Each layer is developed as part of the same system, from the treatment of evidence and reference data to the way results reach laboratory review.
Genomic infrastructure
Locally indexed reference data, parallel processing, controlled environments and versioned analytical dependencies.
Clinical systems
Software that turns these methods into reviewable workflows for laboratories, geneticists and clinical teams.
We develop the methods behind genomic interpretation
Our work addresses how genomic evidence is admitted, classified, prioritised and presented for clinical review. Helena develops methodologies for deterministic variant classification, structural variation and agentic interpretation, and contributes these ideas through publications, preprints and technical documentation.
View researchEvidence admissibility and deterministic classification
A framework that keeps model output outside the class calculation and places human authorization where evidence enters the classifier.
Real-world performance methodology
Evaluation methods for concordance, change attribution and failure analysis against documented laboratory comparators.
Work with us
We at Helena Bioinformatics work with laboratories, universities and research organisations on genomic interpretation, validation and clinical implementation.
