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.