These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
203 related articles for article (PubMed ID: 26411868)
21. PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity. Lee TY; Bretaña NA; Lu CT BMC Bioinformatics; 2011 Jun; 12():261. PubMed ID: 21703007 [TBL] [Abstract][Full Text] [Related]
22. PredCSO: an ensemble method for the prediction of S-sulfenylation sites in proteins. Deng L; Xu X; Liu H Mol Omics; 2018 Aug; 14(4):257-265. PubMed ID: 29942948 [TBL] [Abstract][Full Text] [Related]
23. dbGSH: a database of S-glutathionylation. Chen YJ; Lu CT; Lee TY; Chen YJ Bioinformatics; 2014 Aug; 30(16):2386-8. PubMed ID: 24790154 [TBL] [Abstract][Full Text] [Related]
24. iSulf-Cys: Prediction of S-sulfenylation Sites in Proteins with Physicochemical Properties of Amino Acids. Xu Y; Ding J; Wu LY PLoS One; 2016; 11(4):e0154237. PubMed ID: 27104833 [TBL] [Abstract][Full Text] [Related]
25. Carboxylator: incorporating solvent-accessible surface area for identifying protein carboxylation sites. Lu CT; Chen SA; Bretaña NA; Cheng TH; Lee TY J Comput Aided Mol Des; 2011 Oct; 25(10):987-95. PubMed ID: 22038416 [TBL] [Abstract][Full Text] [Related]
26. Incorporating substrate sequence motifs and spatial amino acid composition to identify kinase-specific phosphorylation sites on protein three-dimensional structures. Su MG; Lee TY BMC Bioinformatics; 2013; 14 Suppl 16(Suppl 16):S2. PubMed ID: 24564522 [TBL] [Abstract][Full Text] [Related]
27. SuccSite: Incorporating Amino Acid Composition and Informative k-spaced Amino Acid Pairs to Identify Protein Succinylation Sites. Kao HJ; Nguyen VN; Huang KY; Chang WC; Lee TY Genomics Proteomics Bioinformatics; 2020 Apr; 18(2):208-219. PubMed ID: 32592791 [TBL] [Abstract][Full Text] [Related]
28. SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models. Wang X; Li C; Li F; Sharma VS; Song J; Webb GI BMC Bioinformatics; 2019 Nov; 20(1):602. PubMed ID: 31752668 [TBL] [Abstract][Full Text] [Related]
29. Computational methods for ubiquitination site prediction using physicochemical properties of protein sequences. Cai B; Jiang X BMC Bioinformatics; 2016 Mar; 17():116. PubMed ID: 26940649 [TBL] [Abstract][Full Text] [Related]
30. A New Scheme to Characterize and Identify Protein Ubiquitination Sites. Nguyen VN; Huang KY; Huang CH; Lai KR; Lee TY IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(2):393-403. PubMed ID: 26887002 [TBL] [Abstract][Full Text] [Related]
31. ViralPhos: incorporating a recursively statistical method to predict phosphorylation sites on virus proteins. Huang KY; Lu CT; Bretaña N; Lee TY; Chang TH BMC Bioinformatics; 2013; 14 Suppl 16(Suppl 16):S10. PubMed ID: 24564381 [TBL] [Abstract][Full Text] [Related]
32. DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder. Khan ZU; Pi D Protein Pept Lett; 2021; 28(6):708-721. PubMed ID: 33267753 [TBL] [Abstract][Full Text] [Related]
33. Identification and characterization of lysine-methylated sites on histones and non-histone proteins. Lee TY; Chang CW; Lu CT; Cheng TH; Chang TH Comput Biol Chem; 2014 Jun; 50():11-8. PubMed ID: 24560580 [TBL] [Abstract][Full Text] [Related]
34. Proteome-Wide Analysis of Cysteine S-Sulfenylation Using a Benzothiazine-Based Probe. Fu L; Liu K; Ferreira RB; Carroll KS; Yang J Curr Protoc Protein Sci; 2019 Feb; 95(1):e76. PubMed ID: 30312022 [TBL] [Abstract][Full Text] [Related]
35. Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions. Su MG; Weng JT; Hsu JB; Huang KY; Chi YH; Lee TY BMC Syst Biol; 2017 Dec; 11(Suppl 7):132. PubMed ID: 29322920 [TBL] [Abstract][Full Text] [Related]
36. PGluS: prediction of protein S-glutathionylation sites with multiple features and analysis. Zhao X; Ning Q; Ai M; Chai H; Yin M Mol Biosyst; 2015 Mar; 11(3):923-9. PubMed ID: 25599514 [TBL] [Abstract][Full Text] [Related]
37. dbSNO: a database of cysteine S-nitrosylation. Lee TY; Chen YJ; Lu CT; Ching WC; Teng YC; Huang HD; Chen YJ Bioinformatics; 2012 Sep; 28(17):2293-5. PubMed ID: 22782549 [TBL] [Abstract][Full Text] [Related]
38. Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs. Chen YZ; Tang YR; Sheng ZY; Zhang Z BMC Bioinformatics; 2008 Feb; 9():101. PubMed ID: 18282281 [TBL] [Abstract][Full Text] [Related]
39. Prediction of pupylation sites using the composition of k-spaced amino acid pairs. Tung CW J Theor Biol; 2013 Nov; 336():11-7. PubMed ID: 23871866 [TBL] [Abstract][Full Text] [Related]
40. N-Ace: using solvent accessibility and physicochemical properties to identify protein N-acetylation sites. Lee TY; Hsu JB; Lin FM; Chang WC; Hsu PC; Huang HD J Comput Chem; 2010 Nov; 31(15):2759-71. PubMed ID: 20839302 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]