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.
159 related articles for article (PubMed ID: 34413898)
1. Accurate Identification of Antioxidant Proteins Based on a Combination of Machine Learning Techniques and Hidden Markov Model Profiles. Shen Z; Liu T; Xu T Comput Math Methods Med; 2021; 2021():5770981. PubMed ID: 34413898 [TBL] [Abstract][Full Text] [Related]
2. HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection. Sang X; Xiao W; Zheng H; Yang Y; Liu T Comput Math Methods Med; 2020; 2020():1384749. PubMed ID: 32300371 [TBL] [Abstract][Full Text] [Related]
3. StackedEnC-AOP: prediction of antioxidant proteins using transform evolutionary and sequential features based multi-scale vector with stacked ensemble learning. Rukh G; Akbar S; Rehman G; Alarfaj FK; Zou Q BMC Bioinformatics; 2024 Aug; 25(1):256. PubMed ID: 39098908 [TBL] [Abstract][Full Text] [Related]
4. AOPs-SVM: A Sequence-Based Classifier of Antioxidant Proteins Using a Support Vector Machine. Meng C; Jin S; Wang L; Guo F; Zou Q Front Bioeng Biotechnol; 2019; 7():224. PubMed ID: 31620433 [TBL] [Abstract][Full Text] [Related]
5. PredDBP-Stack: Prediction of DNA-Binding Proteins from HMM Profiles using a Stacked Ensemble Method. Wang J; Zheng H; Yang Y; Xiao W; Liu T Biomed Res Int; 2020; 2020():7297631. PubMed ID: 32352006 [TBL] [Abstract][Full Text] [Related]
6. HMMs in Protein Fold Classification. Lampros C; Papaloukas C; Exarchos T; Fotiadis DI Methods Mol Biol; 2017; 1552():13-27. PubMed ID: 28224488 [TBL] [Abstract][Full Text] [Related]
7. ANOX: A robust computational model for predicting the antioxidant proteins based on multiple features. Sun D; Liu Z; Mao X; Yang Z; Ji C; Liu Y; Wang S Anal Biochem; 2021 Oct; 631():114257. PubMed ID: 34043981 [TBL] [Abstract][Full Text] [Related]
8. A Composite Approach to Protein Tertiary Structure Prediction: Hidden Markov Model Based on Lattice. Peyravi F; Latif A; Moshtaghioun SM Bull Math Biol; 2019 Mar; 81(3):899-918. PubMed ID: 30536158 [TBL] [Abstract][Full Text] [Related]
9. Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile. Liu T; Zheng X; Wang J Biochimie; 2010 Oct; 92(10):1330-4. PubMed ID: 20600567 [TBL] [Abstract][Full Text] [Related]
10. ANPrAod: Identify Antioxidant Proteins by Fusing Amino Acid Clustering Strategy and Xi Q; Wang H; Yi L; Zhou J; Liang Y; Zhao X; Zuo Y Comput Math Methods Med; 2021; 2021():5518209. PubMed ID: 33927782 [TBL] [Abstract][Full Text] [Related]
11. iAPSL-IF: Identification of Apoptosis Protein Subcellular Location Using Integrative Features Captured from Amino Acid Sequences. Tang Y; Xie L; Chen L Int J Mol Sci; 2018 Apr; 19(4):. PubMed ID: 29652843 [TBL] [Abstract][Full Text] [Related]
12. Identification of antioxidants from sequence information using naïve Bayes. Feng PM; Lin H; Chen W Comput Math Methods Med; 2013; 2013():567529. PubMed ID: 24062796 [TBL] [Abstract][Full Text] [Related]
13. Prediction of protein binding sites in protein structures using hidden Markov support vector machine. Liu B; Wang X; Lin L; Tang B; Dong Q; Wang X BMC Bioinformatics; 2009 Nov; 10():381. PubMed ID: 19925685 [TBL] [Abstract][Full Text] [Related]
14. Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model. Emdadi A; Eslahchi C BMC Bioinformatics; 2021 Jan; 22(1):33. PubMed ID: 33509079 [TBL] [Abstract][Full Text] [Related]
15. A highly accurate protein structural class prediction approach using auto cross covariance transformation and recursive feature elimination. Li X; Liu T; Tao P; Wang C; Chen L Comput Biol Chem; 2015 Dec; 59 Pt A():95-100. PubMed ID: 26460680 [TBL] [Abstract][Full Text] [Related]
16. Sequence-based protein structure prediction using a reduced state-space hidden Markov model. Lampros C; Costas Papaloukas ; Exarchos TP; Yorgos Goletsis ; Fotiadis DI Comput Biol Med; 2007 Sep; 37(9):1211-24. PubMed ID: 17161834 [TBL] [Abstract][Full Text] [Related]
17. Combined prediction of transmembrane topology and signal peptide of beta-barrel proteins: using a hidden Markov model and genetic algorithms. Zou L; Wang Z; Wang Y; Hu F Comput Biol Med; 2010 Jul; 40(7):621-8. PubMed ID: 20488436 [TBL] [Abstract][Full Text] [Related]
18. Identifying Antioxidant Proteins by Using Optimal Dipeptide Compositions. Feng P; Chen W; Lin H Interdiscip Sci; 2016 Jun; 8(2):186-191. PubMed ID: 26345449 [TBL] [Abstract][Full Text] [Related]
19. Predicting Protein-Protein Interactions via Random Ferns with Evolutionary Matrix Representation. Li Y; Wang Z; You ZH; Li LP; Hu X Comput Math Methods Med; 2022; 2022():7191684. PubMed ID: 35242211 [TBL] [Abstract][Full Text] [Related]
20. Using Weighted Extreme Learning Machine Combined With Scale-Invariant Feature Transform to Predict Protein-Protein Interactions From Protein Evolutionary Information. Li J; Shi X; You ZH; Yi HC; Chen Z; Lin Q; Fang M IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(5):1546-1554. PubMed ID: 31940546 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]