---
license: mit
tags:
  - biology
  - protein-classification
  - microalgae
  - genomics
  - nanoGPT
datasets:
  - custom
pipeline_tag: text-classification
---

# Model Card: algaGPT

## Overview

**Name:** algaGPT
**Type:** Causal language model for protein sequence classification
**Base:** nanoGPT (Andrej Karpathy)
**Task:** Binary classification of microalgal vs. contaminant protein sequences
**Mode:** TI-inclusive (full-length sequences)

## Training

- **Data:** ~58.6M protein sequences (1:1 algal:contaminant ratio)
- **Algal sources:** 166 microalgal genomes across 10 phyla
- **Contaminant sources:** Bacterial, archaeal, and fungal sequences from NCBI nr

## Performance

| Metric | Score |
|--------|-------|
| Recall | >99% |
| Speed vs BLASTP+ | ~10,701× faster |

## Usage

Input a protein sequence; model generates a classification tag (algal/conta (contaminant)) via next-token prediction.


## Citation

Nelson DR, Jaiswal AK, Ismail NS, Mystikou A, Salehi-Ashtiani K. Pan-microalgal dark proteome mapping via interpretable deep learning and synthetic chimeras. *Patterns*. 2024;6(11).

## Contact

Kourosh Salehi-Ashtiani
ksa3@nyu.edu