You will get a Drug-Target Affinity Prediction Machine Learning Model
Project details
I offer an end-to-end Machine Learning pipeline optimized for Drug-Target Affinity (DTA) prediction, helping researchers and biotech clients accelerate virtual screening. Using a robust framework, I process small molecule SMILES strings into molecular descriptors and target proteins into sequence-based features.
What sets this project apart is its flexibility: it includes traditional Scikit-learn baselines alongside advanced PyTorch Multi-Layer Perceptron (MLP) architectures to model complex chemical-biological interactions accurately. Whether you need to evaluate novel compounds against known targets or train a custom deep learning network from scratch, I deliver fully scaled workflows evaluated with industry-standard metrics like MSE and Concordance Index. You will receive clear, optimized code or an optional dashboard setup tailored to your discovery pipeline.
What sets this project apart is its flexibility: it includes traditional Scikit-learn baselines alongside advanced PyTorch Multi-Layer Perceptron (MLP) architectures to model complex chemical-biological interactions accurately. Whether you need to evaluate novel compounds against known targets or train a custom deep learning network from scratch, I deliver fully scaled workflows evaluated with industry-standard metrics like MSE and Concordance Index. You will receive clear, optimized code or an optional dashboard setup tailored to your discovery pipeline.
Machine Learning Tools
Python, PyTorch, scikit-learn, XGBoostWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$700
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Model Documentation
(+ 2 Days)
+$50About Rahma
AI | Data Science
Cairo, Egypt - 8:02 am local time
Steps for completing your project
After purchasing the project, send requirements so Rahma can start the project.
Delivery time starts when Rahma receives requirements from you.
Rahma works on your project following the steps below.
Revisions may occur after the delivery date.
Project Steps
We clean SMILES and FASTA sequences, convert them into Morgan Fingerprints and Amino Acid Composition vectors, train traditional ML baselines and PyTorch deep learning models, evaluate with MSE and Concordance Index, and deliver packaged code.