Update README.md

README.md

@@ -3,4 +3,67 @@ license: apache-2.0
 pipeline_tag: tabular-regression
 tags:
 - biology
----
+---
+
+# NexaBio: Advanced Protein Structure Prediction Models
+
+**NexaBio** is a sophisticated two-stage model suite designed for high-accuracy protein structure prediction from amino acid sequences. It comprises two complementary models:
+
+- **NexaBio_1**: A Convolutional Neural Network (CNN) and Bidirectional LSTM (BiLSTM) model for secondary structure prediction.
+- **NexaBio_2**: A Variational Autoencoder (VAE) and Diffusion-based model for tertiary (3D) structure prediction.
+
+NexaBio is a core component of the [Nexa Scientific Model Suite](https://huggingface.co/spaces/Allanatrix/NexaHub), a collection of machine learning models advancing scientific discovery.
+
+## Model Overview
+
+### NexaBio_1: Secondary Structure Prediction
+- **Architecture**: CNN combined with BiLSTM for robust sequence modeling.
+- **Input**: Amino acid sequence (one-hot encoded or embedded).
+- **Output**: Secondary structure classifications (e.g., Helix, Sheet, Coil).
+- **Use Case**: Identification of local structural motifs and protein folding patterns.
+
+### NexaBio_2: Tertiary Structure Prediction
+- **Architecture**: VAE integrated with a Diffusion Model for generative 3D modeling.
+- **Input**: Amino acid sequence (optionally augmented with secondary structure predictions).
+- **Output**: 3D coordinates of protein backbone atoms.
+- **Use Case**: Full tertiary structure prediction for structural analysis and design.
+
+## Applications
+- **Structural Bioinformatics**: Enabling precise protein structure analysis for research.
+- **Drug Discovery**: Supporting protein-ligand interaction studies and therapeutic design.
+- **Protein Engineering**: Facilitating the design of novel proteins for industrial and medical applications.
+- **Synthetic Biology**: Generating protein structures for biotechnological innovation.
+- **Academic Research**: Serving as a tool for educational and exploratory studies.
+
+## Getting Started
+
+### Example Usage
+```python
+from transformers import AutoModel
+
+# Initialize the secondary structure prediction model
+model_sec = AutoModel.from_pretrained("Allanatrix/NexaBio_1")
+
+# Initialize the tertiary structure prediction model
+model_ter = AutoModel.from_pretrained("Allanatrix/NexaBio_2")
+
+# Process an amino acid sequence (refer to model documentation for input formatting)
+```
+
+For comprehensive instructions, including inference APIs and preprocessing details, consult the individual model cards on Hugging Face.
+
+## Citation and License
+If you utilize NexaBio in your research or applications, please cite this repository and include a link to the [Nexa R&D Space](https://huggingface.co/spaces/Allanatrix/NexaR&D).  
+The models and associated code are licensed under the **Boost Software License 1.1 (BSL-1.1)**.
+
+## Part of the Nexa Scientific Ecosystem
+Discover other components of the Nexa Scientific Stack:
+- [Nexa Data Studio](https://huggingface.co/spaces/Allanatrix/NexaDataStudio): Data processing and visualization tools.
+- [Nexa R&D](https://huggingface.co/spaces/Allanatrix/NexaR&D): Research-focused model development environment.
+- [Nexa Infrastructure](https://huggingface.co/spaces/Allanatrix/NexaInfrastructure): Scalable ML deployment solutions.
+- [Nexa Hub](https://huggingface.co/spaces/Allanatrix/NexaHub): Central portal for Nexa resources.
+
+---
+
+*Developed and maintained by [Allan](https://huggingface.co/Allanatrix), an independent machine learning researcher specializing in scientific AI and infrastructure.*
+