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bacteria:t3e:software [2026/05/05 14:23] – rkoebnikbacteria:t3e:software [2026/06/26 10:03] (current) – [Further Reading] rkoebnik
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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]]
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 +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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 ===== Further Reading ===== ===== Further Reading =====
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 +Chan DTC, Agarwal V, Baltrus DA, Dillon MM (2025). Unified classification of the type III secreted effectors of bacterial plant pathogens to advance phytopathology research. Phytopathology 115: 1315-1328. DOI: [[https://doi.org/DOI: 10.1094/PHYTO-02-25-0055-FI|10.1094/PHYTO-02-25-0055-FI]]
  
 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]] 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]]
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 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]]
  
 +Wei L, He S, Fan Z (2026). Machine learning for the prediction of gram-negative bacterial secreted effectors: advances and challenges. Front. Chem. 14: 1810136. DOI: [[https://doi.org/10.3389/fchem.2026.1810136|10.3389/fchem.2026.1810136]]
  
bacteria/t3e/software.1777987416.txt.gz · Last modified: 2026/05/05 14:23 by rkoebnik

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