The CCTOP server's prediction is a consensus of 10 different methods enchanced with available structural and experimental information of any homologous proteins in the TOPDB
was tested on a benchmark set containing 170 proteins with known structure and achieved the highest accuracy among state-of-art and consensus methods.
The HMMTOP transmembrane topology prediction server predicts both the localization of helical transmembrane segments and the topology of transmembrane proteins by utilizing an unsupervised hidden Markov model. In this method the user is allowed to submit additional information about segment localization to enhance the prediction power. This option improves the prediction accuracy as well as helps the interpretation of experimental results, i.e. in epitope insertion experiments.
TMDET algorithm determines the most possible localization of the membrane relative to the protein structure by using the protein 3D structure only, and gives the annotation of the membrane embedded part of the sequence. This web interface of the TMDET algorithm allow scientists to determine the membrane localization of structural data prior
to deposition or to analyze model structures.
DAS-TMfilter is a modification of the dense alignment surface (DAS) transmembrane helix prediction method that achieves a substantial decrease in the false positive error rate in. The modified DAS method, the DAS-TMfilter algorithm, has an unchanged high sensitivity for TM segments (~95% detected in a learning set of 128 documented transmembrane proteins). At the same time, the selectivity measured over a non-redundant set of 526 soluble proteins with known 3D structure is ~99%, mainly because a large number of falsely predicted single membrane-pass proteins are eliminated by the DAS-TMfilter algorithm.
Phobius is a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states.
PSORT-B includes new analytical modules designed to capitalize on new discoveries and observations in protein sorting, and benefits from a training dataset of over 1400 proteins of known localization. Its focus is on precision over recall to faciliate accurate predictions, at the expense of not making as many predictions as other methods may make.
The Localizome server predicts TM helix number and TM topology of a eukaryotic protein and presents the result as an intuitive graphic representation. It utilizes hmmpfam to detect the presence of Pfam domains
, and a prediction algorithm, Phobius
, to predict the TMhelices. The result are combined and checked against the TM topology rules stored in a protein domain databases called LocaloDom.