156 related articles for article (PubMed ID: 25843215)
1. Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.
Zhao X; Ning Q; Chai H; Ma Z
J Theor Biol; 2015 Jun; 374():60-5. PubMed ID: 25843215
[TBL] [Abstract][Full Text] [Related]
2. Succinylation Site Prediction Based on Protein Sequences Using the IFS-LightGBM (BO) Model.
Zhang L; Liu M; Qin X; Liu G
Comput Math Methods Med; 2020; 2020():8858489. PubMed ID: 33224267
[TBL] [Abstract][Full Text] [Related]
3. Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.
Chen Z; Liu X; Li F; Li C; Marquez-Lago T; Leier A; Akutsu T; Webb GI; Xu D; Smith AI; Li L; Chou KC; Song J
Brief Bioinform; 2019 Nov; 20(6):2267-2290. PubMed ID: 30285084
[TBL] [Abstract][Full Text] [Related]
4. Machine learning-based approaches for ubiquitination site prediction in human proteins.
Pourmirzaei M; Ramazi S; Esmaili F; Shojaeilangari S; Allahvardi A
BMC Bioinformatics; 2023 Nov; 24(1):449. PubMed ID: 38017391
[TBL] [Abstract][Full Text] [Related]
5. Accurately Predicting Glutarylation Sites Using Sequential Bi-Peptide-Based Evolutionary Features.
Arafat ME; Ahmad MW; Shovan SM; Dehzangi A; Dipta SR; Hasan MAM; Taherzadeh G; Shatabda S; Sharma A
Genes (Basel); 2020 Aug; 11(9):. PubMed ID: 32878321
[TBL] [Abstract][Full Text] [Related]
6. PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features.
Nilamyani AN; Auliah FN; Moni MA; Shoombuatong W; Hasan MM; Kurata H
Int J Mol Sci; 2021 Mar; 22(5):. PubMed ID: 33800121
[TBL] [Abstract][Full Text] [Related]
7. Mal-Prec: computational prediction of protein Malonylation sites via machine learning based feature integration : Malonylation site prediction.
Liu X; Wang L; Li J; Hu J; Zhang X
BMC Genomics; 2020 Nov; 21(1):812. PubMed ID: 33225896
[TBL] [Abstract][Full Text] [Related]
8. iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition.
Xu Y; Ding J; Wu LY; Chou KC
PLoS One; 2013; 8(2):e55844. PubMed ID: 23409062
[TBL] [Abstract][Full Text] [Related]
9. PRMxAI: protein arginine methylation sites prediction based on amino acid spatial distribution using explainable artificial intelligence.
Khandelwal M; Rout RK
BMC Bioinformatics; 2023 Oct; 24(1):376. PubMed ID: 37794362
[TBL] [Abstract][Full Text] [Related]
10. iTTCA-RF: a random forest predictor for tumor T cell antigens.
Jiao S; Zou Q; Guo H; Shi L
J Transl Med; 2021 Oct; 19(1):449. PubMed ID: 34706730
[TBL] [Abstract][Full Text] [Related]
11. Leveraging permutation testing to assess confidence in positive-unlabeled learning applied to high-dimensional biological datasets.
Xu S; Ackerman ME
BMC Bioinformatics; 2024 Jun; 25(1):218. PubMed ID: 38898392
[TBL] [Abstract][Full Text] [Related]
12. NTpred: a robust and precise machine learning framework for in silico identification of Tyrosine nitration sites in protein sequences.
Datta S; Nabeel Asim M; Dengel A; Ahmed S
Brief Funct Genomics; 2024 Mar; 23(2):163-179. PubMed ID: 37248673
[TBL] [Abstract][Full Text] [Related]
13. RMTLysPTM: recognizing multiple types of lysine PTM sites by deep analysis on sequences.
Chen L; Chen Y
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38066710
[TBL] [Abstract][Full Text] [Related]
14. GBDT_KgluSite: An improved computational prediction model for lysine glutarylation sites based on feature fusion and GBDT classifier.
Liu X; Zhu B; Dai XW; Xu ZA; Li R; Qian Y; Lu YP; Zhang W; Liu Y; Zheng J
BMC Genomics; 2023 Dec; 24(1):765. PubMed ID: 38082413
[TBL] [Abstract][Full Text] [Related]
15. Deciphering functional roles of protein succinylation and glutarylation using genetic code expansion.
Weyh M; Jokisch ML; Nguyen TA; Fottner M; Lang K
Nat Chem; 2024 Jun; 16(6):913-921. PubMed ID: 38531969
[TBL] [Abstract][Full Text] [Related]
16. GPS-SNO: computational prediction of protein S-nitrosylation sites with a modified GPS algorithm.
Xue Y; Liu Z; Gao X; Jin C; Wen L; Yao X; Ren J
PLoS One; 2010 Jun; 5(6):e11290. PubMed ID: 20585580
[TBL] [Abstract][Full Text] [Related]
17. KbhbXG: A Machine learning architecture based on XGBoost for prediction of lysine β-Hydroxybutyrylation (Kbhb) modification sites.
Chen L; Liu L; Su H; Xu Y
Methods; 2024 Jul; 227():27-34. PubMed ID: 38679187
[TBL] [Abstract][Full Text] [Related]
18. SUMOhydro: a novel method for the prediction of sumoylation sites based on hydrophobic properties.
Chen YZ; Chen Z; Gong YA; Ying G
PLoS One; 2012; 7(6):e39195. PubMed ID: 22720073
[TBL] [Abstract][Full Text] [Related]
19. Identification of metal ion binding sites based on amino acid sequences.
Cao X; Hu X; Zhang X; Gao S; Ding C; Feng Y; Bao W
PLoS One; 2017; 12(8):e0183756. PubMed ID: 28854211
[TBL] [Abstract][Full Text] [Related]
20. Human pol II promoter prediction: time series descriptors and machine learning.
Gangal R; Sharma P
Nucleic Acids Res; 2005; 33(4):1332-6. PubMed ID: 15741185
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]