VirulentHunter

home

VirulentHunter is a novel deep learning framework designed to address the limitations of existing VF identification methods. Traditional methods primarily rely on homology alignment, which can miss novel or divergent VFs and lack effective means for VF functional classification. VirulentHunter works directly from protein sequences, using deep learning models to achieve simultaneous VF identification and classification. We have integrated multiple public resources to build a comprehensive and rigorously annotated VF database, providing a solid foundation for model training and prediction. The application of VirulentHunter will drive in-depth research on microbial pathogenicity, providing new perspectives for studying microbial pathogenicity in both controlled laboratory settings and complex environmental samples.

Recent Projects Status

Project ID Submit Time(UTC) Type Status
ngse372****860c43f8 2026-04-16 06:42 protein Pending
bastosb****33c09e0c 2026-04-16 00:56 protein Pending
chench6****35ab71b3 2026-04-15 02:38 protein Pending
1291593****b5ba8e49 2026-04-13 11:32 protein Pending
flsanto****df45af6f 2026-04-06 13:59 protein Pending
fangyi7****9a4e61e0 2026-04-06 13:35 protein Pending
jjpgasp****39197bbe 2026-04-02 18:05 protein Pending
tparama****1cc4542d 2026-04-02 18:03 protein Pending
jjpgasp****56425448 2026-04-02 18:02 protein Pending
mh119d0****02d5dc48 2026-04-02 02:44 protein Pending
khnsp2m****d1b8b294 2026-03-30 11:37 protein Pending
fangyi3****a67d2338 2026-03-30 07:03 protein Pending
fangyif****cfdf788b 2026-03-30 04:15 protein Pending
heba.al****96c66f76 2026-03-28 13:25 protein Pending
ms14420****df96738f 2026-03-27 13:15 protein Running
cesar.a****4180add0 2026-03-26 20:13 protein Completed
cesar.a****36f7e520 2026-03-26 20:07 protein Completed
tparama****8455ddcc 2026-03-26 16:54 protein Completed
cwoods3****bfc133c1 2026-03-24 19:29 protein Completed
ms144e7****4e737a16 2026-03-24 19:02 protein Completed

Tutorial

Here, we present VirulentHunter, a novel deep learning framework for simultaneous VF identification and classification directly from protein sequences. We constructed a comprehensive, curated VF database by integrating diverse public resources and rigorously expanding VF category annotations. Benchmarking demonstrates that VirulentHunter significantly outperforms existing methods, particularly for VFs lacking detectable homology.

Step 1: Navigate to the Search Tab

Upon clicking the Search tab, you will see the interface shown below:

1. Supported Input Data Types:

2. Sequence Input Box:
For small datasets (protein sequences or bacterial strain genomes), directly paste your sequences into this box. Note: This feature is unavailable for metagenomic data.

3. File Upload Box:
For larger datasets (bacterial strain genomes or metagenomic data), you can upload your data in the FASTA format.

4. Email Input Box (Critical):
Enter your email address so that we can send you a message when the job is finished.

5. Additional Notes:
Brief reminders and instructions are displayed to guide your workflow.

information

Step 2: Monitor Task Progress via the Status Tab

Click the Status tab to view the real-time progress of your tasks.

information

Step 3: Task Summary and Real-Time Monitoring:

After a task begins running, users will receive a task summary notification via email.
Click the "View Results" button to access the real-time monitoring page for detailed progress tracking.

information information

Step 4: Accessing Task Results:

Once the task is completed, the system automatically redirects you to the results page.

information

Source code:

https://github.com/mini-ops996/VirulentHunter

Contact

If you have problems with the web server or submit a bug, you can contact Jian Ouyang ().Please contact Dr. Chen () for comments on our website features or for adding new features or data.

Declaration of interest

This tool is for academic purposes and research use only. Any commercial use is subject for authorization from East China Nomral University (ECNU). Please contact us at .