MCMBB: Markov Chain
Model for Beta Barrels
MCMBB is a fast algorithm, which discriminates beta-barrel outer
membrane proteins from globular proteins and from alpha-helical
membrane proteins. The algorithm is based on a 1st order Markov Chain
model, which captures the alternating pattern of
hydrophilic-hydrophobic residues occurring in the membrane-spanning
beta-strands of beta-barrel outer membrane proteins. The model achieves
high accuracy in discriminating outer membrane proteins, since it can
discriminate beta-barrel outer membrane with a correct classification
rate of 90.08% and the globular proteins with a correct
classification rate of 92.67%. When submitting alpha-helical membrane
proteins, the method shows an accuracy of 100%.
A score greater than zero, indicates that the protein is more likely to
be a beta-barrel outer membrane protein, whereas a result lower than
zero, indicates that the protein is probable not a beta-barrel.
You may enter up to 1000 sequences in Fasta format.
Bagos PG, Liakopoulos TD, Hamodrakas SJ.
Finding beta-barrel outer membrane
proteins with a markov chain model.
WSEAS Transactions on Biology and
Biomedicine, 2004, 2(1)