Six Core Scientific Disciplines
7DNA R&D spans six interconnected computational disciplines. Every engagement draws from validated methodology, domain expertise and scientific software purpose-built for the task.
What We Research & Build
Our six disciplines are not silos, they intersect. A drug discovery project may draw on bioinformatics, molecular docking and biomedical AI simultaneously. We work across them fluidly.
Tools We Work With
Our stack spans from specialised molecular simulation software to general scientific computing and AI frameworks. We choose tools based on scientific appropriateness, not convenience.
Molecular Modelling
- AutoDock Vina / 4
- GROMACS
- PyMol
- Schrödinger Suite
- Open Babel
- RDKit
Bioinformatics
- BLAST / HMMER
- DESeq2 / edgeR
- Bioconductor
- STRING / Cytoscape
- GSEA / ClusterProfiler
- Galaxy / Nextflow
AI & Machine Learning
- TensorFlow / Keras
- PyTorch
- Scikit-learn
- DeepChem
- Hugging Face Transformers
- XGBoost / LightGBM
Neuroimaging
- FSL / FreeSurfer
- SPM12
- nilearn / nibabel
- NetworkX
- MRtrix3
- AFNI
Partner With Our Research Team
7DNA R&D engagements range from focused computational analyses to long-term research partnerships. We embed in your project as a computational team, not as an external vendor.
- →Targeted analysis, a focused computational study, deliverable within weeks.
- →Research programme, extended collaboration with co-authorship and method development.
- →Platform development, building a computational tool or platform for your organisation.
What to Expect
We scope your scientific question and identify the right computational approach.
A clear scope, methodology, timeline and cost, no ambiguity.
Rigorous computation with regular updates and transparent reporting.
Reports, datasets, code, visualisations, publication-ready outputs.
Have a computational biology challenge?
Tell us about it. Our scientific team will scope an approach within days.