Update README.md

README.md

@@ -1,6 +1,9 @@
 # Multi-output DNA Structure Regressor (PyTorch)
 
-This repository contains a PyTorch MLP that predicts multiple structural targets from engineered DNA features.
+## Description
+This model is a **multi-output DNA structure regressor** built and trained from scratch in **PyTorch**.  
+It predicts six structural stability metrics — including Minimum Free Energy (MFE), number of base pairs, mean stem length, number of stems, number of hairpins, and number of internal loops — directly from engineered DNA sequence features.  
+Trained on the [aedupuga/2025-scaffold-structures] dataset, the model provides a fast, lightweight alternative to more complex and time-consuming simulation tools like **NUPACK**, enabling near-instant predictions for plasmid stability analysis.
 
 ## Model
 - **Architecture:** 3-layer MLP (512→256→128, dropout 0.3)
@@ -34,4 +37,8 @@ pip install torch numpy
 python inference.py
 ```
 
-Ensure to apply any preprocessing (e.g., scaling, SVD) used during training.
+Ensure to apply any preprocessing (e.g., scaling, SVD) used during training.
+
+## Limitations
+- Performance is less reliable for shorter DNA strands, as the training data primarily consists of longer plasmid sequences.  
+- The model is intended for **educational and exploratory research use**, not for experimental or clinical validation.