The BioInfoX mark 13 nodes and 24 links, drawn in 1,656 points.
Service 07
AI and cheminformatics
Predict how a molecule will behave before anyone makes it: molecular descriptors, QSAR models and interpretable machine learning for drug screening and biomarker discovery. Typically 5 to 7 days.
What we do
The work, step by step
- 01
Molecular descriptors
Physicochemical and structural descriptors calculated for your compound set.
- 02
QSAR modelling
Predictive models trained and validated on your data, with their performance reported honestly.
- 03
Interpretable machine learning
Leakage-free pipelines with XGBoost and SHAP that show which features drive a prediction.
- 04
AI-assisted screening
Machine learning and neural networks to prioritise compounds for docking and dynamics.
You receive
- Descriptor and prediction tables
- Model performance and validation results
- Interpretation plots
- The code and a written methods and results section
Typical turnaround
5–7 days depending on the data
Counted from the day we receive your files. Larger studies get their own timeline with the quote. All turnaround times
Tools
Python and R, XGBoost and SHAP, artificial neural networks and Biopython.
Who works on it
Muhammad Zohaib, with the BioInfoX research team. We take full responsibility for every analysis we perform.
Start
Send us your system and your question.
Structures, sequences or data, your research question and your deadline. We reply with the scope, the timeline and a quote.