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 |Effectidor II |T3E prediction |[[https://effectidor.tau.ac.il/|https://effectidor.tau.ac.il]] |Wagner //et al.//, 2025  | |Effectidor II |T3E prediction |[[https://effectidor.tau.ac.il/|https://effectidor.tau.ac.il]] |Wagner //et al.//, 2025  |
 |PLM-T3SE |T3E prediction |  |Gao //et al.//, 2025  | |PLM-T3SE |T3E prediction |  |Gao //et al.//, 2025  |
-|Effectidor |T3E prediction |[[https://effectidor.tau.ac.il/|https://effectidor.tau.ac.il]] |Wagner //et al.//, 2022a  | 
 |Effectidor |T3E prediction |[[https://effectidor.tau.ac.il/|https://effectidor.tau.ac.il]] |Wagner //et al.//, 2022b  | |Effectidor |T3E prediction |[[https://effectidor.tau.ac.il/|https://effectidor.tau.ac.il]] |Wagner //et al.//, 2022b  |
 +|Effectidor |T3E prediction |[[https://effectidor.tau.ac.il/|https://effectidor.tau.ac.il]] |Wagner //et al.//, 2022a  |
 |DeepT3 2.0 |T3E prediction |[[http://advintbioinforlab.com/deept3/|http://advintbioinforlab.com/deept3/]] |Jing //et al.//, 2021  | |DeepT3 2.0 |T3E prediction |[[http://advintbioinforlab.com/deept3/|http://advintbioinforlab.com/deept3/]] |Jing //et al.//, 2021  |
 +|EP3 |T3E prediction |lab.malab.cn/~lijing/EP3.html |Li //et al.//, 2021  |
 |DeepT3_4 |T3E prediction |[[https://github.com/jingry/autoBioSeqpy/tree/2.0/examples/T3T4|github.com/jingry/autoBioSeqpy/tree/2.0/examples/T3T4]] |Yu //et al.//, 2021  | |DeepT3_4 |T3E prediction |[[https://github.com/jingry/autoBioSeqpy/tree/2.0/examples/T3T4|github.com/jingry/autoBioSeqpy/tree/2.0/examples/T3T4]] |Yu //et al.//, 2021  |
 +|iT3SE-PX |T3E prediction |Datasets and the source codes available at [[https://github.com/taigangliu/iT3SE-PX|https://github.com/taigangliu/iT3SE-PX]] |Ding //et al.//, 2021  |
 |T3SEpp |T3E prediction |[[http://www.szu-bioinf.org/T3SEpp/|www.szu-bioinf.org/T3SEpp]] |Hui //et al.//, 2020  | |T3SEpp |T3E prediction |[[http://www.szu-bioinf.org/T3SEpp/|www.szu-bioinf.org/T3SEpp]] |Hui //et al.//, 2020  |
-|ACNNT3 |T3E prediction |Source code available at: [[https://github.com/Lijiesky/ACNNT3|https://github.com/Lijiesky/ACNNT3]] |Li //et al.//, 2020a  | +|ACNNT3 |T3E prediction |Source code available at: [[https://github.com/Lijiesky/ACNNT3|https://github.com/Lijiesky/ACNNT3]] |Li //et al.//, 2020  | 
-|EP3 |T3E prediction |[[http://lab.malab.cn/~lijing/EP3.html|lab.malab.cn/~lijing/EP3.html]] |Li //et al.//, 2020b  | +|PrediTALE |TAL effector target prediction |galaxy.informatik.uni-halle.de |Erkes //et al.//, 2019  |
-|PrediTALE |TAL effector target prediction |[[http://galaxy.informatik.uni-halle.de|galaxy.informatik.uni-halle.de]] |Erkes //et al.//, 2019  |+
 |Phylogenetic profiling |T3E prediction |[[http://www.iib.unsam.edu.ar/orgsissec/|www.iib.unsam.edu.ar/orgsissec/]] |Zalguizuri //et al.//, 2019  | |Phylogenetic profiling |T3E prediction |[[http://www.iib.unsam.edu.ar/orgsissec/|www.iib.unsam.edu.ar/orgsissec/]] |Zalguizuri //et al.//, 2019  |
 |WEDeepT3 |T3E prediction |[[https://bcmi.sjtu.edu.cn/~yangyang/WEDeepT3.html|bcmi.sjtu.edu.cn/~yangyang/WEDeepT3.html]] |Fu & Yang, 2019 | |WEDeepT3 |T3E prediction |[[https://bcmi.sjtu.edu.cn/~yangyang/WEDeepT3.html|bcmi.sjtu.edu.cn/~yangyang/WEDeepT3.html]] |Fu & Yang, 2019 |
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 |GenSET |T3E prediction |  |Hobbs //et al.//, 2016  | |GenSET |T3E prediction |  |Hobbs //et al.//, 2016  |
 |pEffect |T3E prediction |[[https://services.bromberglab.org/peffect/|services.bromberglab.org/peffect]] |Goldberg //et al.//, 2016  | |pEffect |T3E prediction |[[https://services.bromberglab.org/peffect/|services.bromberglab.org/peffect]] |Goldberg //et al.//, 2016  |
-|QueTAL |Suite for the functional and phylogenetic comparison of TAL effectors |[[http://bioinfo-web.mpl.ird.fr/cgi-bin2/quetal/quetal.cgi|bioinfo-web.mpl.ird.fr/cgi-bin2/quetal/quetal.cgi]] |Pérez-Quintero //et al.//, 2015  |+|QueTAL |Suite for the functional and phylogenetic comparison of TAL effectors |bioinfo-web.mpl.ird.fr/cgi-bin2/quetal/quetal.cgi |Pérez-Quintero //et al.//, 2015  |
 |HMM-LDA |T3E prediction |  |Yang & Qi, 2014 | |HMM-LDA |T3E prediction |  |Yang & Qi, 2014 |
-|Talvez |TAL effector target prediction |[[http://bioinfo-web.mpl.ird.fr/cgi-bin2/talvez/talvez.cgi|bioinfo-web.mpl.ird.fr/cgi-bin2/talvez/talvez.cgi]] |Pérez-Quintero //et al.//, 2013  |+|Talvez |TAL effector target prediction |bioinfo-web.mpl.ird.fr/cgi-bin2/talvez/talvez.cgi |Pérez-Quintero //et al.//, 2013  |
 |TALgetter |TAL effector target prediction |[[http://galaxy.informatik.uni-halle.de/|galaxy.informatik.uni-halle.de]] |Grau //et al.//, 2013  | |TALgetter |TAL effector target prediction |[[http://galaxy.informatik.uni-halle.de/|galaxy.informatik.uni-halle.de]] |Grau //et al.//, 2013  |
 |T3SPs |T3E prediction |cic.scu.edu.cn/bioinformatics/T3SPs.zip **(outdated)**   |Yang //et al.//, 2013  | |T3SPs |T3E prediction |cic.scu.edu.cn/bioinformatics/T3SPs.zip **(outdated)**   |Yang //et al.//, 2013  |
 |cSIEVE |T3E prediction |  |Hovis //et al.//, 2013  | |cSIEVE |T3E prediction |  |Hovis //et al.//, 2013  |
 |T3_MM |T3E prediction |biocomputer.bio.cuhk.edu.hk/softwares/T3_MM (R package), biocomputer.bio.cuhk.edu.hk/T3DB/T3_MM.php **(outdated)**   |Wang //et al.//, 2013  | |T3_MM |T3E prediction |biocomputer.bio.cuhk.edu.hk/softwares/T3_MM (R package), biocomputer.bio.cuhk.edu.hk/T3DB/T3_MM.php **(outdated)**   |Wang //et al.//, 2013  |
-|BEAN |T3E prediction |[[http://systbio.cau.edu.cn/bean/|systbio.cau.edu.cn/bean/]] |Dong //et al.//, 2013; Dong //et al.//, 2015  | +|BEAN |T3E prediction |systbio.cau.edu.cn/bean/ |Dong //et al.//, 2013; Dong //et al.//, 2015  | 
-|RalstoT3Edb |T3E prediction & database |[[http://iant.toulouse.inra.fr/T3E|iant.toulouse.inra.fr/T3E]] |Peeters //et al.//, 2013; Sabbagh //et al.//, 2019  |+|RalstoT3Edb |T3E prediction & database |iant.toulouse.inra.fr/T3E |Peeters //et al.//, 2013; Sabbagh //et al.//, 2019  |
 |TALE-NT |TAL effector target prediction |[[https://boglab.plp.iastate.edu|boglab.plp.iastate.edu]] |Doyle //et al.//, 2012  | |TALE-NT |TAL effector target prediction |[[https://boglab.plp.iastate.edu|boglab.plp.iastate.edu]] |Doyle //et al.//, 2012  |
 |T3DB |T3E database |biocomputer.bio.cuhk.edu.hk/T3DB/ **(outdated)**   |Wang //et al.//, 2012  | |T3DB |T3E database |biocomputer.bio.cuhk.edu.hk/T3DB/ **(outdated)**   |Wang //et al.//, 2012  |
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 Arnold R, Brandmaier S, Kleine F, Tischler P, Heinz E, Behrens S, Niinikoski A, Mewes HW, Horn M, Rattei T (2009). Sequence-based prediction of type III secreted proteins. PLoS Pathog. 5: e1000376. DOI: [[https://doi.org/10.1371/journal.ppat.1000376|10.1371/journal.ppat.1000376]] Arnold R, Brandmaier S, Kleine F, Tischler P, Heinz E, Behrens S, Niinikoski A, Mewes HW, Horn M, Rattei T (2009). Sequence-based prediction of type III secreted proteins. PLoS Pathog. 5: e1000376. DOI: [[https://doi.org/10.1371/journal.ppat.1000376|10.1371/journal.ppat.1000376]]
 +
 +Ding C, Han H, Li Q, Yang X, Liu T (2021). iT3SE-PX: identification of bacterial type III secreted effectors using PSSM profiles and XGBoost feature selection. Comput. Math. Methods Med. 2021: 6690299. DOI: [[https://doi.org/10.1155/2021/6690299|10.1155/2021/6690299]]
  
 Dong X, Lu X, Zhang Z (2015). BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors. Database (Oxford) 2015: bav064. DOI: [[https://doi.org/10.1093/database/bav064|10.1093/database/bav064]] Dong X, Lu X, Zhang Z (2015). BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors. Database (Oxford) 2015: bav064. DOI: [[https://doi.org/10.1093/database/bav064|10.1093/database/bav064]]
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 Kampenusa I, Zikmanis P (2010). Distinguishable codon usage and amino acid composition patterns among substrates of leaderless secretory pathways from proteobacteria. Appl. Microbiol. Biotechnol. 86: 285-293. DOI: [[https://doi.org/10.1007/s00253-009-2423-8|10.1007/s00253-009-2423-8]] Kampenusa I, Zikmanis P (2010). Distinguishable codon usage and amino acid composition patterns among substrates of leaderless secretory pathways from proteobacteria. Appl. Microbiol. Biotechnol. 86: 285-293. DOI: [[https://doi.org/10.1007/s00253-009-2423-8|10.1007/s00253-009-2423-8]]
  
-Li J, Li Z, Luo J, Yao Y (2020a). ACNNT3: Attention-CNN framework for prediction of sequence-based bacterial type III secreted effectors. Comput. Math. Methods Med. 2020: 3974598. DOI: [[https://doi.org/10.1155/2020/3974598|10.1155/2020/3974598]]+Li J, Li Z, Luo J, Yao Y (2020). ACNNT3: Attention-CNN framework for prediction of sequence-based bacterial type III secreted effectors. Comput. Math. Methods Med. 2020: 3974598. DOI: [[https://doi.org/10.1155/2020/3974598|10.1155/2020/3974598]]
  
-Li J, Wei L, Guo F, Zou Q (2020b). EP3: an ensemble predictor that accurately identifies type III secreted effectors. Brief. Bioinform., in press (bbaa008). DOI: [[https://doi.org/10.1093/bib/bbaa008|10.1093/bib/bbaa008]]+Li J, Wei L, Guo F, Zou Q (2021). EP3: an ensemble predictor that accurately identifies type III secreted effectors. Brief. Bioinform. 22: 1918-1928. DOI: [[https://doi.org/10.1093/bib/bbaa008|10.1093/bib/bbaa008]]
  
 Lindeberg M, Stavrinides J, Chang JH, Alfano JR, Collmer A, Dangl JL, Greenberg JT, Mansfield JW, Guttman DS (2005). Proposed guidelines for a unified nomenclature and phylogenetic analysis of type III Hop effector proteins in the plant pathogen //Pseudomonas syringae//. Mol. Plant Microbe Interact. 18: 275-282. DOI: [[https://doi.org/10.1094/MPMI-18-0275|10.1094/MPMI-18-0275]] Lindeberg M, Stavrinides J, Chang JH, Alfano JR, Collmer A, Dangl JL, Greenberg JT, Mansfield JW, Guttman DS (2005). Proposed guidelines for a unified nomenclature and phylogenetic analysis of type III Hop effector proteins in the plant pathogen //Pseudomonas syringae//. Mol. Plant Microbe Interact. 18: 275-282. DOI: [[https://doi.org/10.1094/MPMI-18-0275|10.1094/MPMI-18-0275]]
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 Teper D, Burstein D, Salomon D, Gershovitz M, Pupko T, Sessa G (2016). Identification of novel //Xanthomonas euvesicatoria// type III effector proteins by a machine-learning approach. Mol. Plant Pathol. 17: 398-411. DOI: [[https://doi.org/10.1111/mpp.12288|10.1111/mpp.12288]] Teper D, Burstein D, Salomon D, Gershovitz M, Pupko T, Sessa G (2016). Identification of novel //Xanthomonas euvesicatoria// type III effector proteins by a machine-learning approach. Mol. Plant Pathol. 17: 398-411. DOI: [[https://doi.org/10.1111/mpp.12288|10.1111/mpp.12288]]
  
-Wagner N, Alburquerque M, Ecker N, Dotan E, Zerah B, Pena MM, Potnis N, Pupko T (2022a). Natural language processing approach to model the secretion signal of type III effectors. Front. Plant Sci. 13: 1024405. DOI: [[https://doi.org/10.3389/fpls.2022.1024405|10.3389/fpls.2022.1024405]]+Wagner N, Alburquerque M, Ecker N, Dotan E, Zerah B, Pena MM, Potnis N, Pupko T (2022b). Natural language processing approach to model the secretion signal of type III effectors. Front. Plant Sci. 13: 1024405. DOI: [[https://doi.org/10.3389/fpls.2022.1024405|10.3389/fpls.2022.1024405]]
  
-Wagner N, Avram O, Gold-Binshtok D, Zerah B, Teper D, Pupko T (2022b). Effectidor: an automated machine-learning based web server for the prediction of type-III secretion system effectors. Bioinformatics 38: 2341-2343. DOI: [[https://doi.org/10.1093/bioinformatics/btac087|10.1093/bioinformatics/btac087]]+Wagner N, Avram O, Gold-Binshtok D, Zerah B, Teper D, Pupko T (2022a). Effectidor: an automated machine-learning based web server for the prediction of type-III secretion system effectors. Bioinformatics 38: 2341-2343. DOI: [[https://doi.org/10.1093/bioinformatics/btac087|10.1093/bioinformatics/btac087]]
  
 Wagner N, Baumer E, Lyubman I, Shimony Y, Bracha N, Martins L, Potnis N, Chang JH, Teper D, Koebnik R, Pupko T (2025). Effectidor II: A pan-genomic AI-based algorithm for the prediction of type III secretion system effectors. Bioinformatics 41: btaf272. DOI: [[https://doi.org/10.1093/bioinformatics/btaf272|10.1093/bioinformatics/btaf272]] Wagner N, Baumer E, Lyubman I, Shimony Y, Bracha N, Martins L, Potnis N, Chang JH, Teper D, Koebnik R, Pupko T (2025). Effectidor II: A pan-genomic AI-based algorithm for the prediction of type III secretion system effectors. Bioinformatics 41: btaf272. DOI: [[https://doi.org/10.1093/bioinformatics/btaf272|10.1093/bioinformatics/btaf272]]
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 ===== Further Reading ===== ===== Further Reading =====
 +
 +Hui X, Chen Z, Zhang J, Lu M, Cai X, Deng Y, Hu Y, Wang Y (2021). Computational prediction of secreted proteins in gram-negative bacteria. Comput. Struct. Biotechnol. J. 19: 1806-1828. DOI: [[https://doi.org/10.1016/j.csbj.2021.03.019|10.1016/j.csbj.2021.03.019]]
  
 Noël LD, Denancé N, Szurek B (2013). Predicting promoters targeted by TAL effectors in plant genomes: from dream to reality. Front. Plant Sci. 4: 333. DOI: [[https://doi.org/10.3389/fpls.2013.00333|10.3389/fpls.2013.00333]] Noël LD, Denancé N, Szurek B (2013). Predicting promoters targeted by TAL effectors in plant genomes: from dream to reality. Front. Plant Sci. 4: 333. DOI: [[https://doi.org/10.3389/fpls.2013.00333|10.3389/fpls.2013.00333]]
  
  
bacteria/t3e/software.1749118956.txt.gz · Last modified: 2025/06/05 11:22 by rkoebnik

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