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| ANTISOMA: Reduction of the Aggregation Propensity of Monoclonal Antibodies. |
GNOMM: Automated building of LPS-containing bacterial Outer Membranes for Molecular Dynamics simulations. |
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| GprotPRED:Detection of distinct Galpha families, Gbeta and Ggamma subunits of heterotrimeric G-proteins using profile Hidden Markov Models (pHMMs). |
MBPpred:Prediction of Membrane lipid-Binding Proteins using profile Hidden Markov Models.
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| HMMpTM:A Hidden Markov Model method for the topology prediction of alpha-helical transmembrane proteins that incorporates phosphorylation and glycosylation sites prediction. |
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| AMYL-PRED:A consensus prediction method for identifying possible amyloidogenic regions in protein sequences.
| AMYL-PRED 2:A Consensus Method for Amyloid Propensity Prediction.
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| PRED-SIGNAL:Prediction of signal peptides in archaea.
| PRED-LIPO:Prediction of Lipoprotein Signal Peptides in Gram-Positive Bacteria with a Hidden Markov Model. |
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| HMM-TM:A Hidden Markov Model method for the topology prediction of alpha-helical membrane proteins that incorporates experimentally derived topological information.
| CW-PRED:Prediction of Cell Wall-Anchored Proteins in Gram+ Bacteria |
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| PRED-TMBB:Predicting and discriminating beta-barrel outer membrane proteins with Hidden Markov Models |
PRED-COUPLE 2:A tool that predicts the coupling specificity of G-protein coupled receptors to G-proteins |
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PredSL:PREDiction of Subcellular Location from the N-terminal Sequence |
PRED-COUPLE:A method that implements refined profile Hidden Markov Models to predict the coupling specificity of G-protein coupled receptors to G-proteins |
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ConBBPRED:Consensus Prediction of TransMembrane Beta-Barrel Proteins |
PRED-GPCR:GPCR Family Classification from sequence alone based on a probabilistic method that uses family-specific profile Hidden Markov Models |
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MCMBB: Discrimination of beta-barrel outer membrane proteins with a Markov chain model |
waveTM: Wavelet-based prediction of transmembrane segments in a-helical membrane proteins |
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PRED-CLASS: A system of cascading neural networks that classifies any protein, given its aminoacid sequence alone, into one of four possible classes: membrane, globular, fibrous, mixed |
CoPreTHi: Combines the results of several methods that Predict Transmembrane regions in a joint prediction Histogram |
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orienTM: Topology Prediction of transmembrane proteins and segments |
PRED-TMR2: PRED-TMR application with Neural Network preprocessing |
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PRED-TMR: Prediction of Transmembrane Segments in proteins based on statistical analysis |
SecStr: Secondary Structure Prediction |
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