190 related articles for article (PubMed ID: 32248222)
1. GPS-Palm: a deep learning-based graphic presentation system for the prediction of S-palmitoylation sites in proteins.
Ning W; Jiang P; Guo Y; Wang C; Tan X; Zhang W; Peng D; Xue Y
Brief Bioinform; 2021 Mar; 22(2):1836-1847. PubMed ID: 32248222
[TBL] [Abstract][Full Text] [Related]
2. Prediction and analysis of protein palmitoylation sites.
Hu LL; Wan SB; Niu S; Shi XH; Li HP; Cai YD; Chou KC
Biochimie; 2011 Mar; 93(3):489-96. PubMed ID: 21075167
[TBL] [Abstract][Full Text] [Related]
3. Improved prediction of palmitoylation sites using PWMs and SVM.
Li YX; Shao YH; Deng NY
Protein Pept Lett; 2011 Feb; 18(2):186-93. PubMed ID: 21054270
[TBL] [Abstract][Full Text] [Related]
4. The prediction of palmitoylation site locations using a multiple feature extraction method.
Shi SP; Sun XY; Qiu JD; Suo SB; Chen X; Huang SY; Liang RP
J Mol Graph Model; 2013 Mar; 40():125-30. PubMed ID: 23419766
[TBL] [Abstract][Full Text] [Related]
5. RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data.
Bandyopadhyay SS; Halder AK; Zaręba-Kozioł M; Bartkowiak-Kaczmarek A; Dutta A; Chatterjee P; Nasipuri M; Wójtowicz T; Wlodarczyk J; Basu S
Int J Mol Sci; 2021 Sep; 22(18):. PubMed ID: 34576064
[TBL] [Abstract][Full Text] [Related]
6. GPS-Uber: a hybrid-learning framework for prediction of general and E3-specific lysine ubiquitination sites.
Wang C; Tan X; Tang D; Gou Y; Han C; Ning W; Lin S; Zhang W; Chen M; Peng D; Xue Y
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35037020
[TBL] [Abstract][Full Text] [Related]
7. CSS-Palm 2.0: an updated software for palmitoylation sites prediction.
Ren J; Wen L; Gao X; Jin C; Xue Y; Yao X
Protein Eng Des Sel; 2008 Nov; 21(11):639-44. PubMed ID: 18753194
[TBL] [Abstract][Full Text] [Related]
8. Prediction of palmitoylation sites using the composition of k-spaced amino acid pairs.
Wang XB; Wu LY; Wang YC; Deng NY
Protein Eng Des Sel; 2009 Nov; 22(11):707-12. PubMed ID: 19783671
[TBL] [Abstract][Full Text] [Related]
9. CSS-Palm: palmitoylation site prediction with a clustering and scoring strategy (CSS).
Zhou F; Xue Y; Yao X; Xu Y
Bioinformatics; 2006 Apr; 22(7):894-6. PubMed ID: 16434441
[TBL] [Abstract][Full Text] [Related]
10. Machine Learning Methods in Prediction of Protein Palmitoylation Sites: A Brief Review.
Li Y; Pu F; Wang J; Zhou Z; Zhang C; He F; Ma Z; Zhang J
Curr Pharm Des; 2021; 27(18):2189-2198. PubMed ID: 33183190
[TBL] [Abstract][Full Text] [Related]
11. Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences.
Chen Z; Zhao P; Li F; Wang Y; Smith AI; Webb GI; Akutsu T; Baggag A; Bensmail H; Song J
Brief Bioinform; 2020 Sep; 21(5):1676-1696. PubMed ID: 31714956
[TBL] [Abstract][Full Text] [Related]
12. A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.
Li L; Luo Q; Xiao W; Li J; Zhou S; Li Y; Zheng X; Yang H
J Bioinform Comput Biol; 2017 Feb; 15(1):1650025. PubMed ID: 27411307
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. PalmPred: an SVM based palmitoylation prediction method using sequence profile information.
Kumari B; Kumar R; Kumar M
PLoS One; 2014; 9(2):e89246. PubMed ID: 24586628
[TBL] [Abstract][Full Text] [Related]
15. HybridSucc: A Hybrid-learning Architecture for General and Species-specific Succinylation Site Prediction.
Ning W; Xu H; Jiang P; Cheng H; Deng W; Guo Y; Xue Y
Genomics Proteomics Bioinformatics; 2020 Apr; 18(2):194-207. PubMed ID: 32861878
[TBL] [Abstract][Full Text] [Related]
16. NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm.
Xue Y; Chen H; Jin C; Sun Z; Yao X
BMC Bioinformatics; 2006 Oct; 7():458. PubMed ID: 17044919
[TBL] [Abstract][Full Text] [Related]
17. Physicochemical sequence characteristics that influence S-palmitoylation propensity.
Reddy KD; Malipeddi J; DeForte S; Pejaver V; Radivojac P; Uversky VN; Deschenes RJ
J Biomol Struct Dyn; 2017 Aug; 35(11):2337-2350. PubMed ID: 27498722
[TBL] [Abstract][Full Text] [Related]
18. GPS 2.1: enhanced prediction of kinase-specific phosphorylation sites with an algorithm of motif length selection.
Xue Y; Liu Z; Cao J; Ma Q; Gao X; Wang Q; Jin C; Zhou Y; Wen L; Ren J
Protein Eng Des Sel; 2011 Mar; 24(3):255-60. PubMed ID: 21062758
[TBL] [Abstract][Full Text] [Related]
19. Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning.
Xu H; Jia P; Zhao Z
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32578842
[TBL] [Abstract][Full Text] [Related]
20. Prediction of Rare Palmitoylation Events in Proteins.
Kumari B; Kumar R; Kumar M
J Comput Biol; 2018 Sep; 25(9):997-1008. PubMed ID: 29963911
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
