⚠️ Unexpected Maintenance Notice
The service will undergo unexpected maintenance on Thursday, March 26th, 2026 at 11:00 AM (CET).
The system may become temporarily unavailable during this time. Running jobs may be interrupted and could be lost.
We strongly recommend avoiding job submissions shortly before the maintenance window.
We apologize for the inconvenience and thank you for your understanding.
BetAware is a web server for TransMembrane β-Barrel (TMBB) detection and topology prediction. Both prediction steps are based on advanced machine-learning methods. For TMBB detection, BetAware exploits a new machine learning approach based on N-to-1 Extreme Learning Machines, while TMBB topology prediction is carried-out using a probabilistic model based on Grammatical-Restrained Hidden Conditional Random Fields, a discriminative framework introduced to address sequence labelling tasks in Bioinformatics.
For details see:
- Savojardo C., Fariselli P., Casadio R., BETAWARE: a machine-learning tool to detect and predict trans-membrane β-barrel proteins in Prokaryotes, Bioinformatics (2013) 29(4): 504-505.
- Savojardo C., Fariselli P., Casadio R., Improving the detection of transmembrane β-barrel chains with N-to-1 Extreme Learning Machines, Bioinformatics (2011) 27 (22): 3123-3128.
- Fariselli P., Savojardo C., Martelli P.L., Casadio R., Grammatical-Restrained Hidden Conditional Random Fields for Bioinformatics Applications, Algorithms for Molecular Biology 2009, 4:13.