METHODS BENCHMARKED IN BENCHMARK SERVER : click to hide
DASTMfilt |
DAS-TMfilter
http://www.enzim.hu/DAS/DAS.html
Cserzo M, Eisenhaber F, Eisenhaber B, Simon I (2004) TM or not TM: transmembrane protein prediction with low false positive rate using DAS-TMfilter. Bioinformatics, 20, 1, 136-137.
PMID 14693825
(uses sequence alignment of membrane protein sequences and hydropathy dot-plots)
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DAS2002 |
DAS2002
http://mendel.imp.ac.at/DAS/
Cserzo M, Eisenhaber F, Eisenhaber B, Simon I (2002) On filtering false positive transmembrane protein predictions. Protein Engineering, 15, 745-752.
PMID 12456873
(uses sequence alignment of membrane protein sequences and hydropathy dot-plots)
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DAS1997l |
DAS1997 (loose)
http://www.sbc.su.se/~miklos/DAS/ cutoff=1.7
Cserzo M, Wallin E, Simon I, von Heijne G, Elofsson A (1997) Prediction of transmembrane alpha-helices in procariotic membrane proteins: the Dense Alignment Surface method. Protein Engineering, 10, 673-676.
PMID 9278280
(uses sequence alignment of membrane protein sequences and hydropathy dot-plots)
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DAS1997s |
DAS1997 (strict)
http://www.sbc.su.se/~miklos/DAS/ cutoff=2.2
Cserzo M, Wallin E, Simon I, von Heijne G, Elofsson A (1997) Prediction of transmembrane alpha-helices in procariotic membrane proteins: the Dense Alignment Surface method. Protein Engineering, 10, 673-676.
PMID 9278280
(uses sequence alignment of membrane protein sequences and hydropathy dot-plots)
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deltaG |
deltaG
http://www.cbr.su.se/DGpred/
Hessa T, Meindl-Beinker N, Bernsel A, Kim J, Sato Y, Lerch M, Lundin C, Nilsson I, White SH, von Heijne G (2007) Molecular code for transmembrane-helix recognition by the Sec61 translocon. Nature, 450, 1026-1030.
PMID 18075582
(uses experimentally derived biophysical residue free energy values for insertion into membranes)
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Eisen(7) |
Eisenberg (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=Eisenberg window=7 cutoff=10, minimum helix length of 10
Eisenberg D, Weiss RM, Terwilliger TC (1982) The helical hydrophobic moment: a measure of the amphiphilicity of a helix. Nature, 299, 371-374.
PMID 7110359
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
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Eisen(11) |
Eisenberg (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=Eisenberg window=11 cutoff=10, minimum helix length of 10
Eisenberg D, Weiss RM, Terwilliger TC (1982) The helical hydrophobic moment: a measure of the amphiphilicity of a helix. Nature, 299, 371-374.
PMID 7110359
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
|
Eisen(19) |
Eisenberg (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=Eisenberg window=19 cutoff=10, minimum helix length of 10
Eisenberg D, Weiss RM, Terwilliger TC (1982) The helical hydrophobic moment: a measure of the amphiphilicity of a helix. Nature, 299, 371-374.
PMID 7110359
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
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ENSEMBLE |
ENSEMBLE (in the MemPype server)
http://mu2py.biocomp.unibo.it/mempype
Martelli PL, Fariselli P, Casadio R. (2003) An ENSEMBLE machine learning approach for the prediction of all-alpha membrane proteins. Bioinformatics, 19, Suppl 1, i205-11.
PMID 12855459
Pierleoni A, Indio V, Savojardo C, Fariselli P, Martelli PL, Casadio R. (2011) MemPype: a pipeline for the annotation of eukaryotic membrane proteins. Nucleic Acids Res, 39(Web Server issue), W375-80.
PMID 21543452
(uses neural network (NN) and hidden Markov models (HMM) trained on membrane protein sequences)
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HMM-TM |
HMM-TM
http://bioinformatics.biol.uoa.gr/HMM-TM/
Bagos PG, Liakopoulos TD, Hamodrakas SJ (2006) Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins. BMC Bioinformatics, 5, 7, 189.
PMID 16597327
(uses hidden Markov model (HMM) trained on membrane protein sequences)
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HMMTOP2 |
HMMTOP2
http://www.enzim.hu/hmmtop/
Tusnády GE, Simon I (1998) Principles governing amino acid composition of integral membrane proteins: applications to topology prediction. Journal of Molecular Biology, 283, 489-506.
PMID 9769220
Tusnády GE, Simon I (2001) The HMMTOP transmembrane topology prediction server. Bioinformatics, 17, 849-850.
PMID 11590105
(uses hidden Markov model (HMM) trained on membrane protein sequences)
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hmmtopS |
HMMTOP (in the TOPCONS-single server)
http://single.topcons.net
Tusnády GE, Simon I (1998) Principles governing amino acid composition of integral membrane proteins: applications to topology prediction. Journal of Molecular Biology, 283, 489-506.
PMID 9769220
Tusnády GE, Simon I (2001) The HMMTOP transmembrane topology prediction server. Bioinformatics 17, 849-850.
PMID 11590105
Hennerdal A, Elofsson A (2011) Rapid membrane protein topology prediction. Bioinformatics 27, 9, 1322-1323.
PMID 21493661
(uses hidden Markov model (HMM) trained on membrane protein sequences)
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KyteD(7) |
Kyte-Doolittle (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=Kyte-Doolittle window=7 cutoff=10, minimum helix length of 10
Kyte J, Doolittle RF (1982) A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology, 157, 105-132.
PMID 7108955
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
|
KyteD(11) |
Kyte-Doolittle (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=Kyte-Doolittle window=11 cutoff=10, minimum helix length of 10
Kyte J, Doolittle RF (1982) A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology, 157, 105-132.
PMID 7108955
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
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KyteD(19) |
Kyte-Doolittle (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=Kyte-Doolittle window=19 cutoff=10, minimum helix length of 10
Kyte J, Doolittle RF (1982) A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology, 157, 105-132.
PMID 7108955
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
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MemBrain |
MemBrain
http://chou.med.harvard.edu/bioinf/MemBrain
Shen H, Chou JJ (2008) MemBrain: improving the accuracy of predicting transmembrane helices. PLoS One. 11, 3, e2399.
PMID 18545655
(uses sequence alignment of membrane protein sequences and machine learning trained on membrane protein sequences)
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MEMSAT-SVM |
MEMSAT-SVM
http://bioinf.cs.ucl.ac.uk/psipred/?program=svmmemsat
Nugent T, Jones DT (2009) Transmembrane protein topology prediction using support vector machines. BMC Bioinformatics, 10, 159.
PMID 19470175
(uses support vector machine (SVM) trained on membrane protein sequences)
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MEMSAT3 |
MEMSAT3
http://bioinf.cs.ucl.ac.uk/psipred/?program=svmmemsat
Jones DT (2007) Improving the accuracy of transmembrane protein topology prediction using evolutionary information. Bioinformatics, 23, 5, 538-544.
PMID 17237066
Jones DT, Taylor WR, Thornton JM (1994) A model recognition approach to the prediction of all-helical membrane protein structure and topology. Biochemistry, 33, 10, 3038-3049.
PMID 8130217
(uses artificial neural network (NN) trained on membrane protein sequences)
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memsatS |
MEMSAT (in the TOPCONS-single server)
http://single.topcons.net
Jones DT, Taylor WR, Thornton JM (1994) A model recognition approach to the prediction of all-helical membrane protein structure and topology. Biochemistry, 33, 3038-3049.
PMID 8130217
Hennerdal A, Elofsson A (2011) Rapid membrane protein topology prediction. Bioinformatics 27, 9, 1322-1323.
PMID 21493661
(uses artificial neural network (NN) trained on membrane protein sequences)
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minnou |
MINNOU
http://minnou.cchmc.org/
Cao B, Porollo A, Adamczak R, Jarrell M, Meller J (2006) Enhanced Recognition of Protein Transmembrane Domains with Prediction-based Structural Profiles. Bioinformatics 22:303-309.
PMID 16293670
(uses biophysical residue properties and solvent exposure of predicted secondary structure determined from multiple sequence alignments)
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OCTOPUS |
OCTOPUS
http://octopus.cbr.su.se/
Viklund H, Elofsson A (2008) OCTOPUS: improving topology prediction by two-track ANN-based preference scores and an extended topological grammar. Bioinformatics, 24, 15, 1662-1668.
PMID 18474507
Viklund H, Bernsel A, Skwark M, Elofsson A (2008) SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology. Bioinformatics, 24, 24, 2928-2929.
PMID 18945683
(uses hidden Markov models (HMM) and artificial neural networks (NN) trained on membrane protein sequences)
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octopusT |
OCTOPUS (in the TOPCONS server)
http://topcons.cbr.su.se/
Viklund H, Elofsson A (2008) OCTOPUS: improving topology prediction by two-track ANN-based preference scores and an extended topological grammar. Bioinformatics, 24, 15, 1662-1668.
PMID 18474507
Viklund H, Bernsel A, Skwark M, Elofsson A (2008) SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology. Bioinformatics, 24, 24, 2928-2929.
PMID 18945683
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses hidden Markov models (HMM) and artificial neural networks (NN) trained on membrane protein sequences)
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OHM(7) |
OHM (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=OHM window=7 cutoff=10, minimum helix length of 10
Sweet RM, Eisenberg D (1983) Correlation of sequence hydrophobicities measures similarity in three-dimensional protein structure. Journal of Molecular Biology, 171, 479-488.
PMID 6663622
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
(uses hidden Markov models (HMM) and artificial neural networks (NN) trained on membrane protein sequences)
|
OHM(11) |
OHM (7,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=OHM window=11 cutoff=10, minimum helix length of 10
Sweet RM, Eisenberg D (1983) Correlation of sequence hydrophobicities measures similarity in three-dimensional protein structure. Journal of Molecular Biology, 171, 479-488.
PMID 6663622
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
|
OHM(19) |
OHM (19,10)
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz EMBOSS 6.4.0 pepinfo method=OHM window=19 cutoff=10, minimum helix length of 10
Sweet RM, Eisenberg D (1983) Correlation of sequence hydrophobicities measures similarity in three-dimensional protein structure. Journal of Molecular Biology, 171, 479-488.
PMID 6663622
Rice P, Longden I, Bleasby A (2000) EMBOSS: the European Molecular Biology open software suite. Trends in Genetics, 16, 276-277.
PMID 10827456
(uses biophysical residue hydropathy values)
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PHDhtm |
PHDhtm (at PBIL)
http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_htm.html
Rost B, Sander C (1994) Combining evolutionary information and neural networks to predict protein secondary structure. Proteins, 19, 55-72.
PMID 8066087
Rost B, Sander C (1993) Prediction of protein secondary structure at better than 70% accuracy. J. Mol. Biol., 232, 584-599.
PMID 8345525
Rost B, Sander C (1993) Improved prediction of protein secondary structure by use of sequence profiles and neural networks. Proc. Natl. Acad. Sci. U.S.A., 90, 7558-7562.
PMID 8356056
Rost B, Casadio R, Fariselli P, Sander C (1995) Transmembrane helices predicted at 95% accuracy. Protein Sci, 4, 3, 521-533.
PMID 7795533
Combet C, Blanchet C, Geourjon C, Deléage G (2000) NPS@: Network Protein Sequence Analysis. TIBS 2000, 3, 291, 147-150.
PMID 10694887
(uses sequence alignment of membrane protein sequences and artificial neural network (NN) trained on membrane protein sequences)
|
PHDThtm |
PHDThtm (at PBIL)
http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_htm.html
Rost B, Sander C (1994) Combining evolutionary information and neural networks to predict protein secondary structure. Proteins, 19, 55-72.
PMID 8066087
Rost B, Sander C (1993) Prediction of protein secondary structure at better than 70% accuracy. J. Mol. Biol., 232, 584-599.
PMID 8345525
Rost B, Sander C (1993) Improved prediction of protein secondary structure by use of sequence profiles and neural networks. Proc. Natl. Acad. Sci. U.S.A., 90, 7558-7562.
PMID 8356056
Rost B, Casadio R, Fariselli P, Sander C (1995) Transmembrane helices predicted at 95% accuracy. Protein Sci, 4, 3, 521-533.
PMID 7795533
Combet C, Blanchet C, Geourjon C, Deléage G (2000) NPS@: Network Protein Sequence Analysis. TIBS 2000, 3, 291, 147-150.
PMID 10694887
(uses sequence alignment of membrane protein sequences and artificial neural network (NN) trained on membrane protein sequences)
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Philius |
Philius
http://www.yeastrc.org/philius/pages/philius/uploadFASTA.jsp
http://www.yeastrc.org/philius/pages/philius/runPhilius.jsp
Reynolds SM, Käll L, Riffle ME, Bilmes JA, Noble WS (2008) Transmembrane topology and signal peptide prediction using dynamic bayesian networks. PLoS Comput Biol, 4, 11, e1000213.
PMID 18989393
(uses dynamic Bayesian network trained on membrane protein sequences)
|
Phobius |
Phobius
http://phobius.cgb.ki.se
Käll L, Krogh A, Sonnhammer ELL (2004) A Combined Transmembrane Topology and Signal Peptide Prediction Method. J Mol Biol, 14, 5, 1027-1036.
PMID 15111065
Käll L, Krogh A, Sonnhammer EL (2007) Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server. Nucleic Acids Res, 35, Web Server issue, W429-432.
PMID 17483518
(uses hidden Markov model (HMM) trained on membrane protein sequences)
|
PolyPhobs |
PolyPhobius
http://phobius.sbc.su.se/poly.html
Käll L, Krogh A, Sonnhammer ELL (2005) An HMM posterior decoder for sequence feature prediction that includes homology information. Bioinformatics, 21, Suppl 1, i251-257.
PMID 15961464
Käll L, Krogh A, Sonnhammer EL (2007) Advantages of combined transmembrane topology and signal peptide prediction--the Phobius web server. Nucleic Acids Res, 35, Web Server issue, W429-432.
PMID 17483518
(uses hidden Markov model (HMM) trained on membrane protein sequences and sequence alignment of membrane protein sequences)
|
PRED-TMR |
PRED-TMR
http://athina.biol.uoa.gr/PRED-TMR/input.html
Pasquier C, Promponas VJ, Palaios GA, Hamodrakas JS, Hamodrakas SJ (1999) A novel method for predicting transmembrane segments in proteins based on a statistical analysis of the SwissProt database: the PRED-TMR algorithm. Protein Engineering, 12, 381-385.
PMID 10360978
(uses statistical analysis of protein database)
|
proT |
PRO-TMHMM (in the TOPCONS server)
http://topcons.cbr.su.se/
Viklund H, Elofsson A (2004) Best alpha-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information. Protein Sci, 13, 7, 1908-1917.
PMID 15215532
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses sequence alignment of membrane protein sequences and hidden Markov model (HMM) trained on membrane protein sequences)
|
prodivT |
PRODIV-TMHMM (in the TOPCONS server)
http://topcons.cbr.su.se/
Viklund H, Elofsson A (2004) Best alpha-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information. Protein Sci, 13, 7, 1908-1917.
PMID 15215532
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses sequence alignment of membrane protein sequences and hidden Markov model (HMM) trained on membrane protein sequences)
|
SCAMPI |
SCAMPI
http://scampi.cbr.su.se/
Bernsel A, Viklund H, Falk J, Lindahl E, von Heijne G, Elofsson A (2008) Prediction of membrane-protein topology from first principles. Proc. Natl. Acad. Sci. USA. 105, 7177-7181.
PMID 18477697
(uses biophysical residue hydropathy values and principles of translocon functioning)
|
SCAMPImaT |
SCAMPI-multi (multiple sequence alignment) (in the TOPCONS server)
http://topcons.cbr.su.se/
Bernsel A, Viklund H, Falk J, Lindahl E, von Heijne G, Elofsson A (2008) Prediction of membrane-protein topology from first principles. Proc. Natl. Acad. Sci. USA. 105, 7177-7181.
PMID 18477697
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses sequence alignment of membrane protein sequences, biophysical residue hydropathy values and principles of translocon functioning)
|
SCAMPIsqS |
SCAMPI-sequence (in the TOPCONS-single server)
http://single.topcons.net
Bernsel A, Viklund H, Falk J, Lindahl E, von Heijne G, Elofsson A (2008) Prediction of membrane-protein topology from first principles. Proc. Natl. Acad. Sci. USA. 105, 7177-7181.
PMID 18477697
Hennerdal A, Elofsson A (2011) Rapid membrane protein topology prediction. Bioinformatics 27, 9, 1322-1323.
PMID 21493661
(uses biophysical residue hydropathy values and principles of translocon functioning)
|
SCAMPIsqT |
SCAMPI-sequence (in the TOPCONS server)
http://topcons.cbr.su.se/
Bernsel A, Viklund H, Falk J, Lindahl E, von Heijne G, Elofsson A (2008) Prediction of membrane-protein topology from first principles. Proc. Natl. Acad. Sci. USA. 105, 7177-7181.
PMID 18477697
Hennerdal A, Elofsson A (2011) Rapid membrane protein topology prediction. Bioinformatics 27, 9, 1322-1323.
PMID 21493661
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses biophysical residue hydropathy values and principles of translocon functioning)
|
SOSUI |
SOSUI
http://bp.nuap.nagoya-u.ac.jp/sosui/sosuiG/sosuigsubmit.html
Hirokawa T, Boon-Chieng S, Mitaku S (1998) SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics, 14, 378-379.
PMID 9632836
Mitaku S, Hirokawa T (1999) Physicochemical factors for discriminating between soluble and membrane proteins: hydrophobicity of helical segments and protein length. Protein Engineering, 11, 953-957.
PMID 10585500
Mitaku S, Hirokawa T, Tsuji T (2002) Amphiphilicity index of polar amino acids as an aid in the characterization of amino acid preference at membrane-water interfaces. Bioinformatics, 18, 608-616.
PMID 12016058
(uses biophysical residue hydropathy values and other physico-chemical properties)
|
SPLIT4 |
SPLIT4
http://split.pmfst.hr/split/4/
Juretic D, Zoranic L, Zucic D (2002) Basic charge clusters and predictions of membrane protein topology. Journal of Chemical Information and Modeling, 42, 620-632.
PMID 12086524
(uses biophysical residue hydropathy values and other physico-chemical properties)
|
stmhmmS |
S-TMHMM (in the TOPCONS-single server)
http://single.topcons.net
Viklund H, Elofsson A (2004) Best alpha-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information. Protein Sci, 13, 7, 1908-1917.
PMID 15215532
(uses hidden Markov model (HMM) trained on membrane protein sequences)
|
SVMtm |
SVMtm
http://ccb.imb.uq.edu.au/svmtm/
Yuan Z, Mattick JS, Teasdale RD (2004) SVMtm: Support vector machines to predict transmembrane segments. Journal of Computational Chemistry, 25, 632-636.
PMID 14978706
(uses support vector machine (SVM) trained on membrane protein sequences)
|
SVMtop |
SVMtop
http://bio-cluster.iis.sinica.edu.tw/~bioapp/SVMtop/
Lo A, Chiu HS, Sung TY, Lyu PC, Hsu WL (2008) Enhanced membrane protein topology prediction using a hierarchical classification method and a new scoring function. J Proteome Res. 7, 2, 487-496.
PMID 18081245
(uses support vector machine (SVM) trained on membrane protein sequences)
|
TMAP |
EMBOSS TMAP
ftp://emboss.open-bio.org/pub/EMBOSS/EMBOSS-6.4.0.tar.gz (TMAP was run without any sequence alignment inputs.)
Persson B, Argos P (1994) Prediction of transmembrane segments in proteins utilising multiple sequence alignments. Journal of Molecular Biology, 237, 182-192.
PMID 8126732
Persson B, Argos P (1996) Topology prediction of membrane proteins. Protein Science, 5, 363-371.
PMID 8745415
(uses sequence alignment of membrane protein sequences)
|
TMHMM2 |
TMHMM Server v. 2.0
http://www.cbs.dtu.dk/services/TMHMM/
Sonnhammer ELL, von Heijne G, Krogh A (1998) A hidden Markov model for predicting transemembrane helices in protein sequences. Proceeding of Sixth International Conference on Intelligent Systems for Molecular Biology, Vol. 5, AAAI/MIT Press, Menlo Park, CA, pp. 175-182.
PMID 9783223
Krogh A, Larsson B, von Heijne G, Sonnhammer ELL (2001) Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. Journal of Molecular Biology, 305, 567-580.
PMID 11152613
(uses hidden Markov model (HMM) trained on membrane protein sequences)
|
TMLOOP |
TMLOOP
http://membraneproteins.swan.ac.uk/TMLOOP
Lasso G, Antoniw JF, Mullins JGL (2006) A combinatorial pattern discovery approach for the prediction of membrane dipping (re-entrant) loops. Bioinformatics 22, 14, e290-e297.
PMID 16873484
(uses combinatorial pattern discovery trained on membrane protein sequences)
|
TMMOD |
TMMOD
http://liao.cis.udel.edu/website/servers/TMMOD/
Kahsay RY, Gao G, Liao L (2005) An improved hidden Markov model for transmembrane protein detection and topology prediction and its applications to complete genomes. Bioinformatics, 21, 9, 1853-1858.
PMID 15691854
(uses hidden Markov model (HMM) trained on membrane protein sequences)
|
TMPRED |
TMPRED
http://www.ch.embnet.org/software/TMPRED_form.html
Hofmann K, Stoffel W (1993) TMbase - a database of membrane spanning proteins segments. Biological Chemistry Hoppe-Seyler, 374, 166.
PMID
(uses statistical analysis of protein database)
|
TOPCONS |
TOPCONS
http://topcons.cbr.su.se/
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses consensus of results of other prediction methods and sequence alignment of membrane protein sequences)
|
TOPCONSs |
TOPCONS-single
http://single.topcons.net/
Hennerdal A, Elofsson A (2011) Rapid membrane protein topology prediction. Bioinformatics 27, 1322-1323.
PMID 21493661
Bernsel A, Viklund H, Hennerdal A, Elofsson A (2009) TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Research, Web Server Issue 37, W465-W468.
PMID 19429891
(uses consensus of results of other prediction methods)
|
TOPPRED2 |
TOPPRED2
ftp://ftp.pasteur.fr/pub/gensoft/projects/toppred/toppred-1.10.tar.gz
von Heijne G (1992) Membrane protein structure prediction, hydrophobicity analysis and the positive-inside rule. Journal of Molecular Biology, 225, 487-494.
PMID 1593632
Claros MG, von Heijne G (1994) TopPred II: an improved software for membrane protein structure predictions. Comput Appl Biosci. 10, 6, 685-686.
PMID 7704669
(uses biophysical residue hydropathy values and other physico-chemical properties)
|
VALPRED |
VALPRED
http://sydney.edu.au/pharmacy/sbio/software/valpred.shtml algorithm=VALPRED
(publication in preparation)
(uses threading and biophysical residue hydropathy values and solvent accessible surface area)
|
VALPRED2 |
VALPRED2
http://sydney.edu.au/pharmacy/sbio/software/valpred.shtml algorithm=VALPRED2
(publication in preparation)
(uses threading and biophysical residue hydropathy values and solvent accessible surface area)
|
waveTM |
waveTM
http://bioinformatics.biol.uoa.gr/waveTM
Pashou EE, Litou ZI, Liakopoulos TD, Hamodrakas SJ (2004) waveTM: wavelet-based transmembrane segment prediction. In Silico Biol, 4, 2, 127-131.
PMID 15107018
(uses biophysical residue hydropathy values and dynamic programming algorithm)
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