244 related articles for article (PubMed ID: 22078363)
1. Meta-analytic approach to the accurate prediction of secreted virulence effectors in gram-negative bacteria.
Sato Y; Takaya A; Yamamoto T
BMC Bioinformatics; 2011 Nov; 12():442. PubMed ID: 22078363
[TBL] [Abstract][Full Text] [Related]
2. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems.
Samudrala R; Heffron F; McDermott JE
PLoS Pathog; 2009 Apr; 5(4):e1000375. PubMed ID: 19390620
[TBL] [Abstract][Full Text] [Related]
3. Computational prediction of type III secreted proteins from gram-negative bacteria.
Yang Y; Zhao J; Morgan RL; Ma W; Jiang T
BMC Bioinformatics; 2010 Jan; 11 Suppl 1(Suppl 1):S47. PubMed ID: 20122221
[TBL] [Abstract][Full Text] [Related]
4. Prediction of type III secretion signals in genomes of gram-negative bacteria.
Löwer M; Schneider G
PLoS One; 2009 Jun; 4(6):e5917. PubMed ID: 19526054
[TBL] [Abstract][Full Text] [Related]
5. Discovery of novel secreted virulence factors from Salmonella enterica serovar Typhimurium by proteomic analysis of culture supernatants.
Niemann GS; Brown RN; Gustin JK; Stufkens A; Shaikh-Kidwai AS; Li J; McDermott JE; Brewer HM; Schepmoes A; Smith RD; Adkins JN; Heffron F
Infect Immun; 2011 Jan; 79(1):33-43. PubMed ID: 20974834
[TBL] [Abstract][Full Text] [Related]
6. Computational approach to predict species-specific type III secretion system (T3SS) effectors using single and multiple genomes.
Hobbs CK; Porter VL; Stow ML; Siame BA; Tsang HH; Leung KY
BMC Genomics; 2016 Dec; 17(1):1048. PubMed ID: 27993130
[TBL] [Abstract][Full Text] [Related]
7. Bacterial Type IV secretion systems: versatile virulence machines.
Voth DE; Broederdorf LJ; Graham JG
Future Microbiol; 2012 Feb; 7(2):241-57. PubMed ID: 22324993
[TBL] [Abstract][Full Text] [Related]
8. Secretion Systems Used by Bacteria to Subvert Host Functions.
Rapisarda C; Fronzes R
Curr Issues Mol Biol; 2018; 25():1-42. PubMed ID: 28875938
[TBL] [Abstract][Full Text] [Related]
9. Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors.
Wang J; Yang B; Leier A; Marquez-Lago TT; Hayashida M; Rocker A; Zhang Y; Akutsu T; Chou KC; Strugnell RA; Song J; Lithgow T
Bioinformatics; 2018 Aug; 34(15):2546-2555. PubMed ID: 29547915
[TBL] [Abstract][Full Text] [Related]
10. An account of in silico identification tools of secreted effector proteins in bacteria and future challenges.
Zeng C; Zou L
Brief Bioinform; 2019 Jan; 20(1):110-129. PubMed ID: 28981574
[TBL] [Abstract][Full Text] [Related]
11. Targeting effectors: the molecular recognition of Type III secreted proteins.
Arnold R; Jehl A; Rattei T
Microbes Infect; 2010 May; 12(5):346-58. PubMed ID: 20178857
[TBL] [Abstract][Full Text] [Related]
12. Analysis of the expression, secretion and translocation of the Salmonella enterica type III secretion system effector SteA.
Cardenal-Muñoz E; Ramos-Morales F
PLoS One; 2011; 6(10):e26930. PubMed ID: 22046414
[TBL] [Abstract][Full Text] [Related]
13. Effective identification of bacterial type III secretion signals using joint element features.
Wang Y; Sun M; Bao H; Zhang Q; Guo D
PLoS One; 2013; 8(4):e59754. PubMed ID: 23593149
[TBL] [Abstract][Full Text] [Related]
14. Genome-wide prediction of bacterial effector candidates across six secretion system types using a feature-based statistical framework.
Dhroso A; Eidson S; Korkin D
Sci Rep; 2018 Nov; 8(1):17209. PubMed ID: 30464223
[TBL] [Abstract][Full Text] [Related]
15. Identification of new secreted effectors in Salmonella enterica serovar Typhimurium.
Geddes K; Worley M; Niemann G; Heffron F
Infect Immun; 2005 Oct; 73(10):6260-71. PubMed ID: 16177297
[TBL] [Abstract][Full Text] [Related]
16. Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches.
Wang J; Yang B; An Y; Marquez-Lago T; Leier A; Wilksch J; Hong Q; Zhang Y; Hayashida M; Akutsu T; Webb GI; Strugnell RA; Song J; Lithgow T
Brief Bioinform; 2019 May; 20(3):931-951. PubMed ID: 29186295
[TBL] [Abstract][Full Text] [Related]
17. A new means to identify type 3 secreted effectors: functionally interchangeable class IB chaperones recognize a conserved sequence.
Costa SC; Schmitz AM; Jahufar FF; Boyd JD; Cho MY; Glicksman MA; Lesser CF
mBio; 2012; 3(1):. PubMed ID: 22334517
[TBL] [Abstract][Full Text] [Related]
18. Sequence-based prediction of type III secreted proteins.
Arnold R; Brandmaier S; Kleine F; Tischler P; Heinz E; Behrens S; Niinikoski A; Mewes HW; Horn M; Rattei T
PLoS Pathog; 2009 Apr; 5(4):e1000376. PubMed ID: 19390696
[TBL] [Abstract][Full Text] [Related]
19. Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles.
Zou L; Nan C; Hu F
Bioinformatics; 2013 Dec; 29(24):3135-42. PubMed ID: 24064423
[TBL] [Abstract][Full Text] [Related]
20. Lost after translation: post-translational modifications by bacterial type III effectors.
Salomon D; Orth K
Curr Opin Microbiol; 2013 Apr; 16(2):213-20. PubMed ID: 23466212
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
