ANTICP3 — Anticancer Protein Prediction
ANTICP3 is a LLM-based tool for binary classification of proteins into Anticancer or Non-Anticancer classes, based solely on their primary amino acid sequences. It leverages the powerful ESM2-t33 transformer model, fine-tuned specifically for anticancer protein prediction.
Developed by Prof. G. P. S. Raghava's Lab, IIIT-Delhi
📄 Please cite: ANTICP3
Features
- Fine-tuned ESM2 model for accurate prediction.
- Accepts input in FASTA format.
- Outputs CSV with predicted labels and probabilities.
- Supports CPU and CUDA for faster inference.
- Easy to integrate into pipelines and large-scale datasets.
Model Details
- Base Model: facebook/esm2_t33_650M_UR50D
- Fine-Tuned On: Anticancer protein dataset
- Classification Type: Binary (Anticancer / Non-Anticancer)
- Output Format: CSV with prediction scores and labels
Installation:
pip install anticp3
Metadata
Release files for anticp3 1.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| anticp3-1.1.1.tar.gz | 12.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| anticp3-1.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.1 MB
Release files / anticp3-1.1.1.tar.gz
| Download URL | anticp3-1.1.1.tar.gz |
|---|---|
| Size | 12.5 MB |
| Tags | Source |
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Release files / anticp3-1.1.1-py3-none-any.whl
| Download URL | anticp3-1.1.1-py3-none-any.whl |
|---|---|
| Size | 12.6 MB |
| Tags | Python 3 |
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twine/6.1.0 CPython/3.10.12
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