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Table 1 Prediction of the topology of the Prokaryotic outer membrane proteins.

From: Grammatical-Restrained Hidden Conditional Random Fields for Bioinformatics applications

Method POV Q2 C(t) Sn(t) Sp(t)
CRF-1 (Vit) 0.26 ± 0.05 0.72 ± 0.01 0.47 ± 0.02 0.59 ± 0.01 0.80 ± 0.01
CRF-1 (Pvit) 0.39 ± 0.05 0.77 ± 0.01 0.54 ± 0.02 0.71 ± 0.01 0.80 ± 0.01
CRF-2 (Vit) 0.34 ± 0.05 0.76 ± 0.01 0.52 ± 0.03 0.63 ± 0.02 0.82 ± 0.02
CRF-2 (Pvit) 0.47 ± 0.05 0.80 ± 0.01 0.60 ± 0.03 0.74 ± 0.02 0.82 ± 0.02
CRF-3 (Vit) 0.29 ± 0.04 0.72 ± 0.01 0.45 ± 0.02 0.60 ± 0.02 0.79 ± 0.01
CRF-3 (Pvit) 0.45 ± 0.04 0.76 ± 0.01 0.52 ± 0.02 0.70 ± 0.02 0.79 ± 0.01
GRHCRF 0.66 ± 0.04 0.85 ± 0.01 0.70 ± 0.03 0.83 ± 0.01 0.84 ± 0.01
HMM-B2TMR 0.58 ± 0.04 0.80 ± 0.01 0.62 ± 0.02 0.82 ± 0.02 0.83 ± 0.01
  1. C(t), Sn(t) and Sp(t) are reported for the transmembrane segments (t).
  2. Vit = Viterbi decoding, Pvit = posterior-Viterbi decoding.
  3. For GRHCRF and HMM-B2TMR we used the posterior-Viterbi decoding.
  4. Models are detailed in the text. Scoring indices are described in Measure of Accuracy section.