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.
158 related articles for article (PubMed ID: 29761520)
21. Investigation and identification of protein carbonylation sites based on position-specific amino acid composition and physicochemical features. Weng SL; Huang KY; Kaunang FJ; Huang CH; Kao HJ; Chang TH; Wang HY; Lu JJ; Lee TY BMC Bioinformatics; 2017 Mar; 18(Suppl 3):66. PubMed ID: 28361707 [TBL] [Abstract][Full Text] [Related]
22. Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines. Taherzadeh G; Zhou Y; Liew AW; Yang Y J Chem Inf Model; 2016 Oct; 56(10):2115-2122. PubMed ID: 27623166 [TBL] [Abstract][Full Text] [Related]
23. Global profiling of protein lysine malonylation in mouse cardiac hypertrophy. Wu LF; Wang DP; Shen J; Gao LJ; Zhou Y; Liu QH; Cao JM J Proteomics; 2022 Aug; 266():104667. PubMed ID: 35788409 [TBL] [Abstract][Full Text] [Related]
24. A deep learning method to more accurately recall known lysine acetylation sites. Wu M; Yang Y; Wang H; Xu Y BMC Bioinformatics; 2019 Jan; 20(1):49. PubMed ID: 30674277 [TBL] [Abstract][Full Text] [Related]
25. A chemical probe for lysine malonylation. Bao X; Zhao Q; Yang T; Fung YM; Li XD Angew Chem Int Ed Engl; 2013 Apr; 52(18):4883-6. PubMed ID: 23533089 [No Abstract] [Full Text] [Related]
26. RF-MaloSite and DL-Malosite: Methods based on random forest and deep learning to identify malonylation sites. Al-Barakati H; Thapa N; Hiroto S; Roy K; Newman RH; Kc D Comput Struct Biotechnol J; 2020; 18():852-860. PubMed ID: 32322367 [TBL] [Abstract][Full Text] [Related]
27. 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]
28. Improved Species-Specific Lysine Acetylation Site Prediction Based on a Large Variety of Features Set. Wuyun Q; Zheng W; Zhang Y; Ruan J; Hu G PLoS One; 2016; 11(5):e0155370. PubMed ID: 27183223 [TBL] [Abstract][Full Text] [Related]
29. Malonylome Analysis Reveals the Involvement of Lysine Malonylation in Metabolism and Photosynthesis in Cyanobacteria. Ma Y; Yang M; Lin X; Liu X; Huang H; Ge F J Proteome Res; 2017 May; 16(5):2030-2043. PubMed ID: 28365990 [TBL] [Abstract][Full Text] [Related]
30. A hybrid feature extraction scheme for efficient malonylation site prediction. Sorkhi AG; Pirgazi J; Ghasemi V Sci Rep; 2022 Apr; 12(1):5756. PubMed ID: 35388017 [TBL] [Abstract][Full Text] [Related]
31. Lysine acetylproteome analysis suggests its roles in primary and secondary metabolism in Saccharopolyspora erythraea. Huang D; Li ZH; You D; Zhou Y; Ye BC Appl Microbiol Biotechnol; 2015 Feb; 99(3):1399-413. PubMed ID: 25487885 [TBL] [Abstract][Full Text] [Related]
32. Malonylome analysis in developing rice (Oryza sativa) seeds suggesting that protein lysine malonylation is well-conserved and overlaps with acetylation and succinylation substantially. Mujahid H; Meng X; Xing S; Peng X; Wang C; Peng Z J Proteomics; 2018 Jan; 170():88-98. PubMed ID: 28882676 [TBL] [Abstract][Full Text] [Related]
33. Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC. Chen G; Cao M; Yu J; Guo X; Shi S J Theor Biol; 2019 Jan; 461():92-101. PubMed ID: 30365945 [TBL] [Abstract][Full Text] [Related]
34. Malonylome analysis of rhizobacterium Bacillus amyloliquefaciens FZB42 reveals involvement of lysine malonylation in polyketide synthesis and plant-bacteria interactions. Fan B; Li YL; Li L; Peng XJ; Bu C; Wu XQ; Borriss R J Proteomics; 2017 Feb; 154():1-12. PubMed ID: 27939684 [TBL] [Abstract][Full Text] [Related]
35. UbiSite: incorporating two-layered machine learning method with substrate motifs to predict ubiquitin-conjugation site on lysines. Huang CH; Su MG; Kao HJ; Jhong JH; Weng SL; Lee TY BMC Syst Biol; 2016 Jan; 10 Suppl 1(Suppl 1):6. PubMed ID: 26818456 [TBL] [Abstract][Full Text] [Related]
36. Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction. López Y; Sharma A; Dehzangi A; Lal SP; Taherzadeh G; Sattar A; Tsunoda T BMC Genomics; 2018 Jan; 19(Suppl 1):923. PubMed ID: 29363424 [TBL] [Abstract][Full Text] [Related]
37. The first identification of lysine malonylation substrates and its regulatory enzyme. Peng C; Lu Z; Xie Z; Cheng Z; Chen Y; Tan M; Luo H; Zhang Y; He W; Yang K; Zwaans BM; Tishkoff D; Ho L; Lombard D; He TC; Dai J; Verdin E; Ye Y; Zhao Y Mol Cell Proteomics; 2011 Dec; 10(12):M111.012658. PubMed ID: 21908771 [TBL] [Abstract][Full Text] [Related]
38. Improved prediction of lysine acetylation by support vector machines. Li S; Li H; Li M; Shyr Y; Xie L; Li Y Protein Pept Lett; 2009; 16(8):977-83. PubMed ID: 19689425 [TBL] [Abstract][Full Text] [Related]
39. A Transfer Learning-Based Approach for Lysine Propionylation Prediction. Li A; Deng Y; Tan Y; Chen M Front Physiol; 2021; 12():658633. PubMed ID: 33967828 [TBL] [Abstract][Full Text] [Related]
40. Prediction of lysine propionylation sites using biased SVM and incorporating four different sequence features into Chou's PseAAC. Ju Z; He JJ J Mol Graph Model; 2017 Sep; 76():356-363. PubMed ID: 28763688 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]