systems-genomics-lab/deeptaxa
A deep learning framework for hierarchical taxonomy classification of 16S rRNA gene sequences
This tool helps microbiologists and researchers accurately identify and classify 16S rRNA gene sequences, which are crucial for understanding microbial communities. You input raw 16S rRNA gene sequences, and it outputs their complete taxonomic classification across seven levels, from domain down to species. It's designed for scientists studying microbial diversity and function.
Use this if you need a robust, hierarchical classification system for 16S rRNA gene sequences, especially if you want to experiment with different deep learning models or interpret classification results.
Not ideal if you're looking for a simple, out-of-the-box tool without needing to engage with deep learning concepts or if your primary data is not 16S rRNA gene sequences.
Stars
9
Forks
1
Language
Python
License
MIT
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/systems-genomics-lab/deeptaxa"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lonePatient/Bert-Multi-Label-Text-Classification
This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text...
mim-solutions/bert_for_longer_texts
BERT classification model for processing texts longer than 512 tokens. Text is first divided...
OctoberChang/X-Transformer
X-Transformer: Taming Pretrained Transformers for eXtreme Multi-label Text Classification
QData/LaMP
ECML 2019: Graph Neural Networks for Multi-Label Classification
illiterate/BertClassifier
基于PyTorch的BERT中文文本分类模型(BERT Chinese text classification model implemented by PyTorch)