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.
262 related articles for article (PubMed ID: 17996106)
1. Glycosylation site prediction using ensembles of Support Vector Machine classifiers. Caragea C; Sinapov J; Silvescu A; Dobbs D; Honavar V BMC Bioinformatics; 2007 Nov; 8():438. PubMed ID: 17996106 [TBL] [Abstract][Full Text] [Related]
2. Lysine acetylation sites prediction using an ensemble of support vector machine classifiers. Xu Y; Wang XB; Ding J; Wu LY; Deng NY J Theor Biol; 2010 May; 264(1):130-5. PubMed ID: 20085770 [TBL] [Abstract][Full Text] [Related]
3. SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition. Melvin I; Ie E; Kuang R; Weston J; Stafford WN; Leslie C BMC Bioinformatics; 2007 May; 8 Suppl 4(Suppl 4):S2. PubMed ID: 17570145 [TBL] [Abstract][Full Text] [Related]
4. 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]
5. Using ensemble SVM to identify human GPCRs N-linked glycosylation sites based on the general form of Chou's PseAAC. Xie HL; Fu L; Nie XD Protein Eng Des Sel; 2013 Nov; 26(11):735-42. PubMed ID: 24048266 [TBL] [Abstract][Full Text] [Related]
6. Computational Prediction of N- and O-Linked Glycosylation Sites for Human and Mouse Proteins. Taherzadeh G; Campbell M; Zhou Y Methods Mol Biol; 2022; 2499():177-186. PubMed ID: 35696081 [TBL] [Abstract][Full Text] [Related]
7. Predicting subcellular localization of proteins using machine-learned classifiers. Lu Z; Szafron D; Greiner R; Lu P; Wishart DS; Poulin B; Anvik J; Macdonell C; Eisner R Bioinformatics; 2004 Mar; 20(4):547-56. PubMed ID: 14990451 [TBL] [Abstract][Full Text] [Related]
8. Nglyc: A Random Forest Method for Prediction of N-Glycosylation Sites in Eukaryotic Protein Sequence. Pugalenthi G; Nithya V; Chou KC; Archunan G Protein Pept Lett; 2020; 27(3):178-186. PubMed ID: 31577193 [TBL] [Abstract][Full Text] [Related]
9. Prediction of N-linked glycosylation sites using position relative features and statistical moments. Akmal MA; Rasool N; Khan YD PLoS One; 2017; 12(8):e0181966. PubMed ID: 28797096 [TBL] [Abstract][Full Text] [Related]
10. Computational identification of ubiquitylation sites from protein sequences. Tung CW; Ho SY BMC Bioinformatics; 2008 Jul; 9():310. PubMed ID: 18625080 [TBL] [Abstract][Full Text] [Related]
11. GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome. Li F; Li C; Wang M; Webb GI; Zhang Y; Whisstock JC; Song J Bioinformatics; 2015 May; 31(9):1411-9. PubMed ID: 25568279 [TBL] [Abstract][Full Text] [Related]
12. ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization. Huang WL; Tung CW; Ho SW; Hwang SF; Ho SY BMC Bioinformatics; 2008 Feb; 9():80. PubMed ID: 18241343 [TBL] [Abstract][Full Text] [Related]
13. iDPGK: characterization and identification of lysine phosphoglycerylation sites based on sequence-based features. Huang KY; Hung FY; Kao HJ; Lau HH; Weng SL BMC Bioinformatics; 2020 Dec; 21(1):568. PubMed ID: 33297954 [TBL] [Abstract][Full Text] [Related]
14. In silico platform for prediction of N-, O- and C-glycosites in eukaryotic protein sequences. Chauhan JS; Rao A; Raghava GP PLoS One; 2013; 8(6):e67008. PubMed ID: 23840574 [TBL] [Abstract][Full Text] [Related]
15. AutoMotif server: prediction of single residue post-translational modifications in proteins. Plewczynski D; Tkacz A; Wyrwicz LS; Rychlewski L Bioinformatics; 2005 May; 21(10):2525-7. PubMed ID: 15728119 [TBL] [Abstract][Full Text] [Related]
16. Remote protein homology detection and fold recognition using two-layer support vector machine classifiers. Muda HM; Saad P; Othman RM Comput Biol Med; 2011 Aug; 41(8):687-99. PubMed ID: 21704312 [TBL] [Abstract][Full Text] [Related]
17. Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. Walia RR; Caragea C; Lewis BA; Towfic F; Terribilini M; El-Manzalawy Y; Dobbs D; Honavar V BMC Bioinformatics; 2012 May; 13():89. PubMed ID: 22574904 [TBL] [Abstract][Full Text] [Related]
18. Predicting protein sumoylation sites from sequence features. Teng S; Luo H; Wang L Amino Acids; 2012 Jul; 43(1):447-55. PubMed ID: 21986959 [TBL] [Abstract][Full Text] [Related]
19. GlycoPP: a webserver for prediction of N- and O-glycosites in prokaryotic protein sequences. Chauhan JS; Bhat AH; Raghava GP; Rao A PLoS One; 2012; 7(7):e40155. PubMed ID: 22808107 [TBL] [Abstract][Full Text] [Related]
20. Predicting DNA-binding sites of proteins from amino acid sequence. Yan C; Terribilini M; Wu F; Jernigan RL; Dobbs D; Honavar V BMC Bioinformatics; 2006 May; 7():262. PubMed ID: 16712732 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]